Methods for determining selectivity of test compounds

ABSTRACT

The invention relates to methods for determining the selectivity of a test compound and related methods such as methods for determining whether a subject suffering from cancer will respond or is responsive to treatment with a test compound or compositions comprising more than one test compound.

The invention relates to methods for determining the selectivity of atest compound and related methods such as methods for determiningwhether a subject suffering from cancer will respond or is responsive totreatment with a test compound. In particular methods comprising thesteps of (a) providing a sample comprising at least two distinguishablesub-populations of cells in a total population of cells; (b) dividingthe sample into at least two parts; (c) incubating at least one partobtained in (b) in the absence of a test compound and at least one partobtained in (b) in the presence of a test compound; (d) determining thenumber of cells in one of the at least two sub-populations that exhibita distinguishable phenotype, relative to the number of cells in thetotal population of cells that exhibit the same phenotype in (i) the atleast one part incubated in the presence of the test compound and (ii)in the at least one part incubated in the absence of the test compound;and (e) determining selectivity of the test compound to induce thephenotype referred to in (d) in the one sub population referred to instep (d) over all other subpopulations by dividing (i) through (ii)wherein the test compound selectively induces the phenotype referred toin (d) if (i) divided through (ii) is greater than 1, preferably greaterthan 1.05, 1.1, 1.5, 2, 3 most preferably 5, and selectively inhibits orreduces the phenotype referred to in (d) if it is less than 1,preferably less than 0.95, 0.9, 0.7, 0.5, 0.3, most preferably less than0.2. The invention also provides for methods for determining whether asubject suffering from cancer will respond or is responsive to treatmentwith a test compound, wherein the method comprises (a) providing asample from the subject comprising at least two sub-populations of cellsin a total population cells, wherein at least one sub-populationcorresponds to cancerous cells and at least one sub-populationscorresponds to non-cancerous cells; (b) dividing the sample into atleast two parts; (c) incubating at least one part obtained in (b) in theabsence of a test compound and at least one part in the presence of atest compound; (d) determining the number of viable cells in at leastone of the sub-populations corresponding to cancer cells relative to thenumber of viable cells in the total population of cells in (i) the atleast one part incubated in the presence of the test compound and (ii)the at least one part incubated in the absence of the test compound; and(e) determining whether the subject will respond or is responsive totreatment with the test compound by dividing (i) through (ii), whereinthe subject will respond or is responsive to treatment if the resultingvalue is less than 1, preferably less than 0.95, 0.9, 0.8, 0.6, 0.4 mostpreferably less than 0.2.

The identification of drugs for the treatment of human and/or animaldiseases requires the identification of molecules that selectivelyinduce a desired biological effect in particular cell types while notaffecting other cells thus causing unwanted side effects. Conversely, adrug that is capable of selectively inducing a desired biological effectin the desired cell type in an individual patient is likely to providesaid patient with a medical benefit. A drug with lower selectivity maycause severe side effects, may require the reduction of the treatmentdose and may consequently not lead to the desired medical outcome.

In the past, drug discovery has relied heavily on the use of cell linemodel systems. It is increasingly understood, however, that these modelsonly incompletely recapitulate complex processes of higher organismswhich often involve the interplay of different cell types. Inparticular, selectivity as the ability to induce an effect only in thedesired target cell type cannot be studied in such systems. A possiblesolution practiced in the art is to test molecules in different celllines independently. However, this does not take into account thepossible interplay of different cell types. Alternatives are theestablishment of co-culture model systems in which different cell linesare mixed to recapitulate a more realistic environment. Additionally,chemical matter can also be tested directly in primary material such asPBMCs or bone marrow comprised of multiple cell types ex vivo. In thecontext of drug discovery and development, efficient methods are thusrequired to measure how chemical matter selectively affects one celltype over others in mixtures of cells comprising at least two differentcell types.

It is also becoming increasingly clear that different patients sufferingfrom the same medical condition may have vastly different responses tothe same medicament. It is estimated that up to 90% of all prescribeddrugs only benefit 25% of the patients.

Treating a patient with a likely ineffective medicament may not onlycause unnecessary suffering due to side effects and lack of medicalbenefit but will also waste precious healthcare financial resources.Methods are thus required to accurately predict treatment outcome forindividual patients in order to enable physicians to give the right drugto the right patient at the right time.

Methods of the art for the personalized prediction of treatment responsecan broadly be divided into methods that infer treatment response fromindirect biomarkers (e.g., inferring from a mutation in BCR-ABL that apatient will likely not respond to Imatinib) and methods that directlymeasure drug action in primary patient material to predict treatmentoutcome (i.e., functional ex vivo drug tests).

Functional ex vivo drug tests known in the art include the MiCK assay(Kravtsov et al., Blood. 92 (3): 968-80), the method described inUS20100298255A1, or the Cell Titer Glo assay of Promega Coporation.These methods focus on testing whether a target cell populationextracted from a patient is responsive to a particular medicament undersuitable ex vivo incubation conditions. Here, we present evidence, thatunlike prior belief in the field, it is insufficient to merely measuredrug response in the target cell population but in fact the selectivityof a drug to affect target cells as opposed to off-target cells isessential to predict treatment outcome (Examples 2-4). Thus, also forthe prediction of clinical drug response using functional ex vivo drugresponse tests, efficient means are required to measure how chemicalmatter (e.g. FDA approved drugs) selectively affect one cell populationover others in mixtures of cells comprising at least two differentsub-population of cells.

Selectivity of a drug to affect one cell population over anotherpopulation is traditionally measured by comparing the concentration atwhich 50% of the desired or on-target effect is achieved (EC50) in thecell population of interest to the concentration at which 50% of thesame effect is achieved in the off-target population of cells.

One approach practiced in the art is to isolate target and off-targetcell populations or provide isolated cell lines representing target andoff-target cell populations and individually measure drug response overdifferent concentrations in these isolated cell populations. Thedisadvantage of this approach is that target cells are not analysed intheir natural environment, which may affect the outcome in various ways.Moreover, if target cells need to be isolated from complex cell mixtures(e.g., PBMCs), this manipulation introduces additional perturbation tothe system that may affect the measurement outcome. Further, effectsthat are dependent on cell-cell interactions through direct physicalinteractions or action at a distance through soluble messengers (e.g.,cells of the immune system clearing damaged but not apoptotic cancercells) cannot be reproduced in isolated cell model systems.

In order to determine selectivity of drugs or other chemical testcompounds in complex mixtures comprised of two or more cell types, novelmethods are required to distinguish between different cell populationsand selectively measure drug effect on each cell populationindividually. The standard method practiced in the art to analysecomplex cell mixtures is flow cytometry. Here, individual cellpopulations can be distinguished and the effect of a test compound canbe measured using fluorescent dyes and markers (e.g., through stainingwith fluorescently labelled antibodies, fluorescent live-deathstaining). Another approach has been described in WO 2016/046346.

In order to determine the EC50 of a chemical test compound such as adrug acting on a particular cell sub-population in a complex mixture ofcells using flow cytometry, the person skilled in the art would countthe cells of the sub-population of interest (i.e., determine theabsolute cell number) exhibiting the desired phenotype upon treatmentwith the chemical compound at typically 4 or more concentrations of thechemical compound, plot the number of cells exhibiting the desiredphenotype upon treatment with the chemical compound againstconcentration of the chemical compound and fit a 4 parameter logistic orother sigmoidal model to determine the EC50. Alternatively, a proxymeasure that is directly proportional to the phenotype such as ATPlevels for total number of viable cells can be used. This is evidencedby numerous prior art documents and application notes such as Hernandezet al., SLAS Technology 2017, Vol. 22(3) 325-337 (here: phenotype islive leukemic cells) or Ross et al. Cancer Research 49, 3776-3782. Jul.15, 1989 and the considerable effort that has been invested intovalidating and optimizing the ability to count absolute cell numbersusing flow cytometry.

In order to determine selectivity of a test compound to affect one celltype over another in a complex mixture of cells, the person skilled inthe art would consequently measure the EC50 of the test compound towardsboth cell populations, take the ratio of the the EC50 values or thedifference of the log EC50 values as the measure of selectivity (c.f.,definition of therapeutic index used by FDA).

However, this approach suffers from major limitations: Absolute cellnumbers are inherently difficult to measure using flow cytometry andalso other single cell analysis techniques. Absolute cell numbers seededinto assay plates may vary significantly in particular when automatedcell dispensing machinery is used. During subsequent staining andwashing steps, cells may be lost differentially from different assaywells. Further, absolute cell quantification typically needs to bebenchmarked against bead standards which introduces another source oferror and represents additional effort. Finally, determination ofselectivity will require the measurement of test compound effect atdifferent test compound concentrations which vastly increases the samplerequirement and assay time.

In view of the foregoing, there is a need in the art for methods fordetermining selectivity of chemical compounds in complex cellularmixtures.

The technical problem to be solved by the present invention is thus theprovision of improved methods for determining selectivity of one or moretest compound(s) and related methods based on the improved determinedselectivity.

The invention; in a first embodiment, thus relates to a method fordetermining the selectivity of a test compound, the method comprisingthe steps:

-   -   (a) providing a sample comprising at least two distinguishable        sub-populations of cells in a total population of cells;    -   (b) dividing the sample into at least two parts;    -   (c) incubating at least one part obtained in step (b),in the        absence of a test compound and at least one part obtained in        step (b) in the presence of a test compound;    -   (d) determining the number of cells in one of the at least two        sub-populations that exhibit a distinguishable phenotype,        relative to the number of cells in the total population of cells        that exhibit the same phenotype in        -   (i) the at least one part incubated in the presence of the            test compound and        -   (ii) in the at least one part incubated in the absence of            the test compound;    -   (e) determining selectivity of the test compound to induce the        phenotype referred to in (d) in the one sub population referred        to in step (d) over all other subpopulations by dividing (i)        through (ii) wherein the test compound selectively induces the        phenotype referred to in (d) if (i) divided through (ii) is        greater than 1, preferably greater than 1.05, 1.1, 1.5, 2, 3        most preferably 5, and selectively inhibits or reduces the        phenotype referred to in (d) if it is less than 1, preferably        less than 0.95, 0.9, 0.7, 0.5, 0.3, most preferably less than        0.2.

Unlike methods practiced in the art for determining the selectivity of atest compound to induce or inhibit a phenotype in one distinguishablecell population over other cell populations in a total population ofcells, the methods of the invention do not require the measurement ofabsolute cell numbers but rely on the measurement of the fraction ofcells with a desired phenotype of a total cell population exhibiting thesame phenotype. As a consequence, the methods of the present inventionare robust towards variations in the exact cell numbers seeded intoassay plates that may vary significantly in particular when automatedcell dispensing machinery is used. The methods of the present inventionare further robust towards cell loss during subsequent staining andwashing steps where cells may be lost differentially from differentassay wells. The methods further do not require to be benchmarkedagainst bead standards which introduces another source of error andrepresents additional effort. The methods of the present invention arethus internally controlled. Also, the methods of the present inventioncan obtain selectivity information with as few as one concentrationpoint of the compound measured whereas competing methods requiremultiple concentration points are measured; see e.g. Example 8.

Further, the methods of the invention unlike methods practiced in theart do not require the separation of cell populations comprising a totalpopulation of cells prior to determining the selectivity of the testcompound with respect to the cell populations comprising the totalpopulation of cells. Thus, the methods of the invention do not only relyon the effect of a test compound on an isolated target cell populationin order to determine its selectivity, but also take into account theinterplay of cells comprised in a complex population of cells.Therefore, the methods of the invention surprisingly allow for themeasurement of test compound, selectivity in mixtures of cells wherebythe resulting selectivity is inherently robust towards variations incell numbers between different measurements, is internally controlledand takes into account the interplay between different cell populationscomprised in a total population of cells.

Further, the methods of the present invention do not depend ondetermining an EC50 from a dose-response curve. This is in contrast tothe methods in the prior art that require the determination of an EC50to measure selectivity. The EC50 is the concentration of a compound atwhich the, half maximum effect induced by the compound or inhibited bythe test compound is obtained. The EC50 is often also called IC50(“inhibitory concentration 50%”) or GI50 (“growth inhibition 50%”)depending on the context. Alternatively, also concentrations at whichother percentages of the effect is achieved or inhibited are sometimesused (e.g., EC90, EC80 etc.). The EC50 is typically obtained bymeasuring response of a cell towards a test compound at 4 or moreconcentrations and fitting a suitable sigmoidal curve to the data. Todetermine selectivity of a compound to affect one cell population overanother, the EC50 of a compound to affect both cell populations has tobe measured independently and the difference in log EC50 is taken as ameasure of selectivity. For the purpose of determining an EC50, ameasurement that is directly proportional to response to a test compoundsuch as the number of cells with a particular phenotype or the magnitudeof an effect are required. Such measurements are inherently sensitive invariation of absolute cell numbers incubated with a test compound priorto measurement of a desired phenotype. Rather, the methods of thepresent invention rely on fractions of cells of one populationexhibiting a particular phenotype of the total number of cells with thesame phenotype to determine selectivity. Therefore, the methods of theinvention do not rely on the quantification of absolute cell numbers andare internally controlled and allow quantification of selectivity oftest compounds by measuring response to test compounds at fewerconcentration points than required by methods in the art that requirethe determination of an EC50 and therefore a full dose-response curve(Example 1). The latter is particularly advantageous when the amount ofsample provided is limited as it is often the case with primary patientsamples.

EC50 values, which lie at the heart of determining selectivity inmethods practiced in the care, cannot be determined from fractions of asubset of cells exhibiting a phenotype of the total number of cellsexhibiting the desired phenotype, as illustrated in Example 12. It istherefore not obvious to a person skilled in the art to use the fractionof cells exhibiting a particular phenotype of the total number of cellsexhibiting the same phenotype to derive information about selectivity.

In contrast to methods of the prior art, in the methods of theinvention, for the purpose of evaluating selectivity of a test compoundto affect one sup-population of cells over another, selectivity of atest compound is determined based on the number of cells of a particularsub population of cells that exhibit a particular phenotype of interestrelative to the number of cells in the total population of cells thatexhibit the same phenotype. The resulting selectivity is thereforeinherently robust towards variations in absolute cell numbers betweendifferent measurements, as illustrated in Example 13, is internallycontrolled and takes into account the interplay between different cellpopulations comprised in a total population of cells. Further, theselectivity can be determined by measuring response of cells to testcompounds at fewer concentration points than required by methods in theart.

Unlike methods in the prior art for determining whether a subjectsuffering from cancer will respond or is responsive to treatment with atest compound, the methods of the invention correlate the effect of atest compound on the cancerous populations of cells comprised in acomplex population of various cell populations from the patient to theeffect of the same test compound on said complex population of cells asa whole. Thus, the methods of the invention not only rely on the effectof a test compound on a target cancer cell population in order todetermine its selectivity and make conclusions about whether a patienttreated with the test compound will or will not respond, butadditionally take into account undesired effects of the test compound onalternative cells comprised in a complex population of cells. In otherwords, the methods of the present invention quantify the selectiveability of an anticancer drug to kill cancerous over non-cancerous cellsin order to determine whether a subject suffering from cancer willrespond or is responsive to treatment with a test compound or drug.Compared to methods described in the prior art that only measure testcompound effect on cancer cells, the methods of the present inventiongive more accurate information about whether a subject suffering fromcancer will respond or is responsive to treatment with a test compoundas illustrated in Examples 2-4. Specifically, as shown in the appendedexamples, the area under the ROC curve (AUROC) value as a measure of thequality by which a method can distinguish two classes using the methodof the present invention was 0.97, whereas using a method according toWO 2016/046346 resulted in an AUROC of only 0.91 and basing it on cellnumber gave an AUROC of 0.86 (see FIG. 5). Similarly, a reducedclassification accuracy was observed in Examples 2 and 3 resulting inFIG. 4. As such, the method of the present invention resulted in aclassification accuracy of 0.85, whereas if drug response was determinedonly based on the sensitivity of cancer cells or the sensitivity of thetotal cell population, a classification accuracy of 0.65 or less wasobtained (FIG. 4, middle and bottom panels, respectively). Based on thecomparative data provided in the present application, it is thus evidentthat the method of the present invention provides an improved accuracy.

Further, unlike methods in the prior art for determining whether asubject suffering from cancer will respond or is responsive to treatmentwith a test compound, the methods of the invention do not rely on thequantification of absolute cell numbers, dose response curves orisolation of cell populations comprising a total population of cells intherefore are more robust towards variation in total cell numbersbetween different measurements, selective loss of cells from individualmeasurements, can take into account the interplay of different cellpopulations that may affect response of a cell population to testcompounds (e.g., recognition of a damaged but not dead cancer cell bycells of the immune system) and requires measurement at lessconcentration points.

The methods of the invention, in step (a), comprise the provision of asample comprising at least two distinguishable sub-populations of cellsin a total population of cells. Within the present invention, the term“distinguishable sub-population” refers to cells that are part of alarger population and can be distinguished from other cells in thepopulation by means of a cell marker. That is, cells of twodistinguishable subgroups may belong to the same or different cell typeas long as the cells show differing expression profiles of cell markers,which makes them distinguishable using imaging techniques such asconfocal microscopy. In order to easily determine whether cells belongto a subgroup of cells, it is preferred to provide cells in form of amonolayer. As shown in the appended Examples, monolayer formation can bedone using a method known in the art. For samples comprising onlynon-adherent cells or mixtures of adherent and non-adherent cells,monolayer formation is done preferably by the method as taught in WO2016/046346. Accordingly, in a preferred embodiment of the invention,the methods of the invention further comprise, subsequent to step (b)and prior to further analysis, the formation of a monolayer comprisingthe cells of the cell sample used. In this respect, the type of the cellsample used in the methods of the present invention is not particularlylimited as long as it comprises at least two distinguishablesub-populations of cells. In a preferred embodiment of the invention,however, the cell sample used is a PBMC sample or a bone-marrow sample.

Cell markers are proteins expressed by a cell of a particular type thatalone or in combination with other proteins allow cells of this type tobe distinguished from other cell types. That is, by using cell markersexpressed on the surface of cells or within (including within thecytoplasm or within an internal membrane) cells comprised in the totalpopulation of cells as used herein, e.g. as comprised in a sampleobtained from a donor, can be distinguished and thus attributed todistinguishable sub-populations. Accordingly, the two or moredistinguishable subgroups of cells are not limited to cells belonging todifferent cell types. Rather, cells of the two or more distinguishablesubgroups may be of the same cell type as long as the subgroups aredistinguishable using cell markers, e.g. those expressed on theirsurface, e.g. cells of the same cell type at different disease stages,and/or cells of the same type but of different activation states and/orcells of the same type but of different differentiation stages.

Peripheral blood mononuclear cells (PBMCs) are blood cells having around nucleus (as opposed to a lobed nucleus). PBMCs compriselymphocytes (B-cells, T-cells (CD4 or CD8 positive), and NK cells),monocytes (dendritic cell and macrophage precursor), macrophages, anddendritic cells. These blood cells are a critical component in theimmune system to fight infection and adapt to intruders. In context ofsome embodiments of the present invention, it is preferred to use ficolldensity gradient purified PBMCs, preferably human PBMCs, for creation ofthe PBMC monolayer of the invention or the cell-culture devicecomprising the PBMC monolayer or for use in the methods provided in someaspects of the present invention. The present invention can be used withany mononuclear cells, In a preferred embodiment, the invention candetermine, but is not limited to determining the selectivity of a testcompound with respect to a target cell comprised in a PBMC orbone-marrow cell sample, i.e. selectivity towards cells within thefollowing groups of cells, and cells within the lineage of the cells,including terminal cell states: Hematopoietic stem cells (including, butnot limited to, common lymphoid progenitor, common myeloid progenitor,and their maturation lineage and terminal states including pro-B-cell,B-cell, double negative t-cells, positive T-cell, plasma-B-cell,NK-cells, monocytes (macrophage, dendritic cells)). These can be found,but not limited to, within peripheral blood, bone marrow (flat bonelocalized), cord blood, spleen, thymus, lymph tissue, and any fluidbuildup result of a disease such as pleural fluid. Cells may be in anyhealthy or diseased state.

PBMCs cells for use in the methods described herein can be isolated fromwhole blood using any suitable method known in the art or describedherein. For example, the protocol described by Panda et al. may be used(Panda, S. and Ravindran, B. (2013). Isolation of Human PBMCs.Bio-protocol 3(3): e323). Preferably, density gradient centrifugation isused for isolation. Such density gradient centrifugation separates wholeblood into components separated by layers, e.g., a top layer of plasma,followed by a layer of PBMCs and a bottom fraction of polymorphonuclearcells (such as neutrophils and eosinophils) and erythrocytes. Thepolymorphonuclear cells can be further isolated by lysing the red bloodcells, i.e. non-nucleated cells. Common density gradients useful forsuch centrifugation include, but are not limited to, Ficoll (ahydrophilic polysaccharide, e.g., Ficoll®-Paque (GE Healthcare, Upsalla,Sweden) and SepMate™ (StemCell Technologies, Inc., Köln, Germany).

Bone-marrow cells for use in the methods described herein can beisolated from bone marrow using any suitable method known in the art. Inparticular, density gradient centrifugation and magnetic beads can beused to separate bone-marrow cells from other components of suchsamples. For example, MACS cell separation reagents may be used(Miltenyi Biotec, Bergisch Gladbach, Germany).

As is known in the art, such isolated cultures may contain a smallpercentage of one or more populations of another cell type, e.g.,non-nucleated cells such as red blood cells. The PBMCs may be furtherisolated and/or purified from such other cell populations as is known inthe art and/or as described herein; for example, methods of lysing redblood cells are commonly use to remove such cells from the isolatedPBMCs. However, the methods of the invention are not reliant on furtherpurification methods, and the isolated PBMCs isolated herein may bedirectly used. Accordingly, the methods disclosed herein may or may notcomprise lysing of red blood cells from within the sample of isolatedPBMCs. However, where present, it is believed that the presence ofnon-nucleated cells, e.g., red blood cells, being generally smaller thanPBMCs, settle on the culture surface below and between the PBMCs, andpotentially interfere with the formation of a monolayer suitable forimaging. Therefore it is preferred that the concentration ofnon-nucleated cells, e.g., red blood cells, relative to PMBCs is betweenabout 500 to 1, more preferably about 250 to 1, most preferably about100 to 1, with the preferential concentration as low as possible. Thatis, it is most preferred that the isolated PBMC sample used in themethods disclosed herein contains less than about 100 non-nucleatedcells, e.g. red blood cells, per PBMC.

Subsequent to providing a sample, in particular a sample comprising atleast two distinguishable sub-populations of cells in a total populationof cells, as detailed above, and in particular a sample comprising PBMCsor bone-marrow cells, the sample is divided into at least two parts.Alternatively, instead of dividing the sample provided in (a), at leasttwo samples of identical origin and type may be provided, i.e. samplesthat require no further division. The two parts may have equal size orbe of different size. However, it is preferred that each of the at leasttwo parts comprises a similar, preferably identical, ratio of cells ofeach distinguishable sub-population.

Subsequently to dividing the sample into at least two parts, at leastone of the parts is incubated in the absence of a test compound, i.e.the test compound whose selectivity is to be determined. That is, thepart is used as control/reference part.

At least one of the remaining parts obtained in step (b) is incubated inpresence of the test compound. In this respect, the test compound or themultiple test compounds is/are not particularly limited as long asit/they are generally suitable for use as pharmaceutical. However, it ispreferred that said test compound(s) is/are selected from compoundsknown to be effective in the treatment of a disease, in particular ahematologic malignancy and/or a malignancy of myeloid and/or lymphoidtissue, inflammatory and autoimmune diseases. Compounds known to beeffective in the treatment of such diseases comprise chemical compoundsand biological compounds, such as, for example, antibodies. Examples ofcompounds known to be effective in the treatment of such diseasesinclude but are not limited to Alemtuzumab, Anagrelide, Arsenictrioxide, Asparaginase, ATRA, Azacitidine, Bendamustin, Blinatumomab,Bortezomib, Bosutinib, Brentuximab vedotin, Busulfan, Ceplene,Chlorambucil, Cladribine, Clofarabine, Cyclophosphamide, Cytarabine,Dasatinib, Daunorubicin, Decitabine, Denileukin diftitox, Dexamethasone,Doxorubicin, Duvelisib, EGCG=Epigallocatechin gallate, Etoposide,Filgrastim, Fludarabine, Gemtuzumab ozogamicin, histaminedihydrochloride, Homoharringtonine, Hydroxyurea, Ibrutinib, Idarubicin,ldelalisib, Ifosfamide, Imatinib, Interferon Alfa-2a, Recombinant,Interferon Alfa-2b, Recombinant, Intravenous Immunoglobulin,L-asparaginase, Lenalidomide, Masitinib, Melphalan, Mercaptopurine,Methotrexate, Midostaurin, Mitoxantrone, MK-3475=Pembrolizumab,Nilotinib, Pegaspargase, Peginterferon alfa-2a, Plerixafor, Ponatinib,Prednisolone, Prednisone, R115777, RAD001 (Everolimus), Rituximab,Ruxolotinib, Selinexor (KPT-330), Sorafenib, Sunitinib, Thalidomide,Topotecan, Tretinoin, Vinblastine, Vincristine, Vorinostat, Zoledronate,ABL001, ABT-199=Venetoclax, ABT-263=Navitoclax, ABT-510, ABT-737,ABT-869=Linifanib, AC220=Quizartinib, AE-941=Neovastat, AG-858, AGRO100,Aminopterin, Asparaginase Erwinia chrysanthemi, AT7519, AT9283, AVN-944,Bafetinib, Bectumomab, Bestatin, beta alethine, Bexarotene, BEZ235, BI2536, Buparlisib (BKM120), Carfilzomib, Carmustine, Ceritinib,CGC-11047, CHIR-258, CHR-2797, CMC-544=Inotuzumab ozogamicin, CMLVAX100,CNF1010, CP-4055, Crenolanib, Crizotinib, Ellagic Acid, Elsamitrucin,Epoetin Zeta, Epratuzumab, FAV-201, Favld, Flavopiridol, G4544,Galiximab, gallium maltolate, Gallium nitrate, Givinostat, GMX1777,GP1-0100, Grn163I, GTI 2040, IDM-4, Interferon alfacon-1, IPH 1101,ISS-1018, Ixabepilone, JQ1, Lestaurtinib, Mechlorethamine, MEDI4736,MGCD-0103, MLN-518=Tandutinib, motexafin gadolinium, Natural alphainterferon, Nelarabine, Obatoclax, Obinutuzumab, OSI-461, Panobinostat,PF-114, PI-88, Pivaloyloxymethyl butyrate, Pixantrone, Pomalidomide,PPI-2458, Pralatrexate, Proleukin, PU-H71, Ranolazine, Rebastinib,Samarium (153sm) lexidronam, SGN-30, Skeletal targeted radiotherapy,Tacedinaline, Tamibarotene, Temsirolimus, Tioguanine, Troxacitabine,Vindesine, VNP 40101M, Volasertib, XL228, hydroxychloroquine(Plaquenil), leflunomide (Arava), methotrexate (Trexall), sulfasalazine(Azulfidine), minocycline (Minocin), abatacept (Orencia), rituximab(Rituxan), tocilizumab (Actemra), anakinra (Kineret), adalimumab(Humira), etanercept (Enbrel), infliximab (Remicade), certolizumab,pegol (Cimzia), golimumab (Simponi), tofacitinib (Xeljanz, Xeljanz XR),baricitinib, celecoxib (Celebrex), ibuprofen (prescription-strength),nabumetone (Relafen), naproxen sodium (Anaprox), naproxen (Naprosyn),piroxicam (Feldene), diclofenac (Voltaren, Diclofenac Sodium XR,Cataflam, Cambia), diflunisal, indomethacin (Indocin), ketoprofen(Orudis, Ketoprofen ER, Oruvail, Actron), etodolac (Lodine), fenoprofen(Nalfon), flurbiprofen, ketorolac (Toradol), meclofenamate, mefenamicacid (Ponstel), meloxicam (Mobic), oxaprozin (Daypro), sulindac(Clinoril), salsalate (Disalcid, Amigesic, Marthritic, Salflex,Mono-Gesic, Anaflex, Salsitab), tolmetin (Tolectin), betamethasone,prednisone (Deltasone, Sterapred, Liquid Pred), dexamethasone (Dexpak,Taperpak, Decadron, Hexadrol), cortisone, hydrocortisone (Cortef,A-Hydrocort), methylprednisolone (Medrol, Methacort, Depopred,Predacorten), prednisolone, cyclophosphamide (Cytoxan), cyclosporine(Gengraf, Neoral, Sandimmune), azathioprine (Azasan, Imuran), andhydroxychloroquine (Plaquenil).

Accordingly, in the methods of the present invention, at least one partof the cell sample is incubated in the absence of the test compound(s)and at least one sample is incubated in the presence of the testcompound(s).

In this respect, in some embodiments of the methods of the invention,cells, in particular PBMCs, are incubated subsequently to isolation at adensity of about 100 cells per mm² growth area to about 30000 cells permm² growth area. Preferably, the cells, in particular PBMCs, areincubated at a density of about 500 cells per mm² growth area to about20000 cells per mm² growth area, about 1000 cells per mm² growth area toabout 10000 cells per mm² growth area, about 1000 cells per mm² growtharea to about 5000 cells per mm² growth area, or about 1000 cells permm² growth area to about 3000 cells per mm² growth area. Most preferablythe cells, in particular PBMCs, are incubated at a density of about 2000cells per mm² growth area. The term “about” shall have the meaning ofwithin 10%, more preferably within 5%, of a given value or range.Accordingly, the cells, in particular PBMCs, are, in some embodiments,incubated in the methods of the invention to have in the culture devicea density of about 100, i.e. from 90 to 110, cells per mm² growth areato about 30000, i.e. 27000 to 33000, cells per mm² growth area. Morepreferably, the cells, in particular PBMCs, are incubated at a densityof about 500, i.e. 450 to 550, cells per mm² growth area to about 20000,i.e. 18000 to 22000, cells per mm² growth area, about 1000, i.e. 900 to1100, cells per mm² growth area to about 10000, i.e. 9000 to 11000,cells per mm² growth area, about 1000, i.e. 900 to 1100, cells per mm²growth area to about 5000, i.e. 4500 to 5500, cells per mm² growth area,or about 1000, i.e. 900 to 1100, cells per mm² growth area to about3000, i.e. 2700 to 3300, cells per mm² growth area. Most preferably thecells, in particular PBMCs, are incubated at a density of about 2000,i.e. 1800 to 2200, cells per mm² growth area.

The number of cells, in particular PBMCs, can be determined usingstandard methods known in the art. In particular, the number of PBMCscan be determined by cell counting using a hemocytometer or the methoddescribed by Chan et al. (Chan et al. (2013) J. Immunol. Methods 388(1-2), 25-32). The number of bone-marrow cells can also be determinedusing methods well known in the art. In particular, bone-marrow cellscan be determined using cell counting. Other cells may also be countedusing methods well-known in the art.

Incubation is carried out in a culture medium. A person skilled in theart is well aware of suitable methods to maintain viability of cells, inparticular PBMCs or bone-marrow cells. However, the culture medium to beused in the methods of the invention is not particularly limited. Inthis regard, medium stands for liquids with nutrients and substancesnecessary for cultivation of cells. Liquid culture media for culturingeucaryotic cells are known to the person skilled in the art (e.g., DMEM,RPMI 1640, etc). Suitable media may be selected depending on the type ofcells to be cultured. For example, PBMCs or bone-marrow cells may becultivated in RPMI 1640 10% FCS. Any suitable media may be chosen,however, media components should be selected that are known to notartificially influence PBMC response and/or bone-marrow cell response.Supplements describe substances to be added to culture media in order toinduce or modify cell function (e.g. cytokines, growth anddifferentiation factors, mitogens, serum). Supplements are known to theperson of skill in the art. One example of a serum commonly used witheukaryotic cells is fetal calf serum. The culture media may further besupplemented with antibiotics, such as penicillin, streptomycin,ciprofloxacin etc. In one embodiment, test substances and/or stimulatoryagents may be added to living cell material in each individual unitseparately. Test substances may be pharmaceutical drugs or drugcomponents. Stimulators may comprise any of the substances which supportmaintenance, growth or differentiation of cells. In a particularembodiment, stimulators are substances which act on immune cells, e.g.by activation of immune cells. Stimulators for activation of immunecells are known from the prior art. Such agents may be polypeptides,peptides or antibodies and other stimulators. For example, OKT-3,interferon-alpha, interferon-beta and interferon-gamma, oligoCPGs,mitogens (e.g. PWM, PHA, LPS), etc. Test substances and stimulators maybe injected into the cell culture medium. Preferably, PBMCs are culturedin RPMI supplemented with FBS/FCS at 10% (preferably but not necessarilyhaving low endotoxin raitings to minimize activation). PBMC cultures mayfurthermore comprise human serum from the PBMC donor.

The term “growth area” as used within the meaning of the inventionrefers to the surface within a culture device upon which cells rest. The“density” as used within the meaning of the invention is the quantity ofcells per unit area of the surface within the device upon which thecells rest. The culture device may be produced of any materialcompatible with cell culture, in particular, non-cytotoxic cell culturetested material. Examples for the material are plastic materials, e.g.,thermoplastic or duroplastic materials. Examples of suitable plasticsare polyethylene, polypropylene, polysulfone,polycarbonate/polyetherethylketone (PEEK) or polytetrafluorethylene(PTFE). In particular, the device is suitable for the culture and/ormaintenance of PBMCs. Typical culture devices known in the art and ofuse in the invention include culture flasks, dishes, plates, andmulti-well plates. Of particular use are multi-well plates, whichprovide the ability to separately maintain multiple cultures, e.g., formultiple perturbations, with minimal material requirements, e.g.,minimal media requirements. Preferred culture devices include 96 wellplates, 384 well plates and 1536 well plates. As known in the art inconnection with imaging analysis of cultures, in particular,fluorescence imaging, it is particularly preferred to use black wallplates specifically designed for imaging that reduce backgroundfluorescence/background optical interference with minimal light scatterand reduced crosstalk. The culture device may be sterilized. In a mostpreferred embodiment, a multiwell imaging plate is used, the plateincluding multiple wells, wherein at least some of the wells comprise afirst chamber, the first chamber being formed by one or more firstsidewalls and a bottom wall; a second chamber, the second chamber beingformed by one or more second sidewalls and including an opening forintroducing liquids, wherein the second chamber is arranged on top ofthe first chamber; an intermediate floor provided between the firstchamber and the second chamber which forms a disturbance blockingstructure; wherein the intermediate floor is provided with at least onethrough hole that provides a liquid connection between the first andsecond chambers; wherein the through hole is configured for a tip of apipette being inserted through the second chamber into the first chamberthrough said through hole.

The device is in particular of use in automated imaging systems andanalysis. Thus, it is preferred that the device/culture device issuitable for use in such systems. In a non-limiting example, the culturedevice may be translucent. Culture dishes and plates of use for imaging,e.g., fluorescent imaging, are well known in the art and arecommercially available. A non-limiting example of a commerciallyavailable culture plate for use in the practice of the invention isCorning® 384-well, tissue-culture treated black lid, clear bottom plates(Corning Inc., Massachusetts, USA) or Corning® 384 Well Flat ClearBottom Black Polystyrene TC-Treated Microplates (Product #3712). Anotherexample is the Perkin Elmer Cellcarrier®.

As outlined above, one surprising technical advantage of the methods ofthe invention is that the methods determine/rely on selectivity of atest compound towards target cells that is determined in an environmentthat more closely represents the natural environment of the target cellswithin a complex population of cells. That is, in the methods of thepresent invention, naturally-occurring cell-cell interactions arepreferably maintained. In this respect, the skilled person is aware ofmeans and methods how to determine/assess/track/verify cell-cellinteractions. In particular, the person skilled in the art candistinguish between natural-occurring cell-cell interactions and thoseintroduced during the preparation of a cell sample. As such, the skilledperson understands that cells of the same type and/or cells of differenttypes interact in a living organism. Moreover, the person skilled in theart understands that cells of distinguishable subgroups of cellscomprised in the total population of cells interact in a livingorganism. In the present invention, it is preferred that the majority ofcells comprised in the cell sample maintain their natural-occurringcell-cell interactions. That is, the majority of cells, in particular atleast 50% of the cells comprised in the cell sample, preferably 60%,65%, 70%, 75%, 80%, 85%, 90%, 95%, or 100% of the cells comprised in thecell sample interact with the same cell or a cell of the same cell typeor a cell of the same distinguishable subgroup as in vivo. Cell-cellinteractions can be verified/assessed/determined using methodswell-known in the art. For example, confocal microscopy can be used toassess/determine/verify whether cell-cell interactions are between cellsinteracting in a natural environment or between cells that do not showinteraction in a natural environment. Such non-natural cell-cellinteractions may be due to, inter alia, cell clumping.

Moreover, in the methods of the present invention, the majority of cellsis preferably found in a physiologically-relevant state, which meansthat preferably 60%, 70%, 80%, 90%, 95% or 100% of the cells are in aphysiologically-relevant state. The above percentages of cells in aphysiologically-relevant state used in the methods of the presentinvention are determined/measured/assessed using methods well-known inthe art. In particular, whether a cell sample comprises cells found in aphysiologically-relevant state is determined by quantification of cellscomprised in the cell sample. This may be done using methods well knownin the art. In particular, quantification may be done through imageanalysis compared to the cells in a reference sample, for example inperipheral blood or bone marrow of a reference individual or multiplereference individuals, e.g. one or more healthy donor(s) where the cellsample, in particular the PBMC or bone-marrow cell sample is derivedfrom a diseased donor. Quantification of cells is a standard diagnostictool. Thresholds of cell subpopulations comprised in cell samples, inparticular PBMCs and/or bone-marrow cells are well documented forhealthy donors and diseased donors. Accordingly, based on differences insamples to be assessed using the means and methods of the presentinvention, the physiological-relevance can be determined. Documentationof cell subpopulations comprised in hematopoietic cells can be found,for example, in Hallek et al. (2008) Blood 111(12). Accordingly,quantification and further means and methods, for example determinationof cell-cell interactions using microscopy, allow the determinationwhether a cell sample represents a physiological-relevant state.

The inventors have provided methods that allow analysis of samplescomprising cells which maintain naturally-occurring cell-cellinteractions and which are mainly found in a physiologically relevantstate. Thus, in a preferred embodiment of the invention, the cells areanalyzed in the form of monolayers. In this respect, it has been foundby the inventors that incubation at the cell densities disclosed above,results in formation of an imageable monolayer of cells, in particularPBMCs or bone-marrow cells. The monolayers are formed subsequent todividing the sample into at least two parts, i.e. step (b) and prior tofurther analysis. Thus, the methods of the present invention allow,inter alfa, imaging and/or microscopic analysis of cell population, inparticular PBMC populations and/or bone-marrow populations. Monolayer asused herein implies a single layer of cells found predominantly withinthe same focal plane of the imaging device, e.g., microscope orautomated camera as is known in the art or described herein. The termsingle layer is used to mean that the cells within this layer form aculture that is predominantly 2-dimensional, i.e., the culture ispredominantly a layer of single cells. That is, within the culture, themajority of the cells are not found resting on or above other cells, andare not found in aggregates (e.g., consisting of groups of cells thatextend above the layer of single cells by comprising cells that rest onor above other cells). Thus, the cell monolayer, in particular PBMCmonolayer within the meaning of the invention preferably comprises ahorizontal layer of cells, in particular PBMC cells having a thicknessof the height of one single cell, in particular PBMC. Likewise, thebone-marrow cell monolayer within the meaning of the inventionpreferably comprises a horizontal layer of bone-marrow cells having athickness of the height of one single bone-marrow cell. As used herein,the term monolayer does not exclude that within the culture vessel cellaggregates or multilayer constructs (i.e., areas having cell cultureswith a height of greater than one cell; in particular PBMC cell or onebone-marrow cell, respectively) or areas without cells may be found.Rather, the term is used to mean that the cultures of the invention willhave the majority of their imageable or visible area (e.g., bymicroscopic methods) consisting of a single layer of cells. This is mosteasily accomplished as providing a single layer of cells on a cellculture surface. However, as the skilled person will appreciate, otherformats of cell samples may also be used in the methods of the presentinvention.

In the case of non-adherent cells that are to be used, for example PBMCsor bone marrow cells, it is known that such cells typically do not formstrong contacts with cell-culture surfaces or strong cell-to-cellcontacts. Therefore, the cell monolayers used in the present invention,in particular the PBMC monolayers used in various aspects of the presentinvention are not envisioned to be necessarily equivalent to monolayersof adherent cells as understood in the art, i.e., comprising a layer ofcells firmly attached, evenly spread, and covering the majority of theculture surface. Rather, in some embodiments, the cell monolayer, inparticular the PBMC monolayer used in the invention may comprisecultures of high density comprising a majority of cells in directcontact with one or more other cells, but not necessarily adhered to theculture surface, or may comprise cultures of low density, wherein cellsare within the monolayer but have no (direct physical) contact with anyother cell in the culture. The cell monolayers used in certain aspectsof the present invention may also comprise cultures of intermediatedensity, having discrete areas wherein cells are in contact with one ormore cells and other areas where the cells exhibit no contact with othercells.

The cells, in particular PBMCs, bone marrow cells, or other adherent-and non-adherent primary cells for use in the methods of the presentinvention may be isolated from a sample obtained from a healthy subject,i.e. not suspected to suffer from a disease or suspected to bepredisposed to a disease, or may be isolated from a sample obtained froma subject known to be suffering from a disease or suspected to sufferfrom a disease. The diagnosis of the disease state of the subject may bemade by standard methods routinely performed by those skilled in theart, e.g., physicians. Such traditional methods may be supplemented orreplaced with the methods of the present invention. For example, inorder to determine whether a subject suffers or is likely to suffer froma disease, a cell-cell interaction pattern is determined that ischaracteristic for the respective disease using samples from subjectsknown to suffer from the disease. Additionally, or alternatively, thecell-cell interaction pattern of a healthy donor may be used todetermine differences that likely are due to the respective disease.Cell interaction pattern here refers to the propensity of one or moredifferent cell types or cell populations to interact with each otherdetermined according to the present invention.

Subsequent to incubation, the number of cells in one of the at least twosub-populations that exhibit a distinguishable phenotype is determined,relative to the number of cells in the total population of cells thatexhibit the same phenotype in (i) the at least one part incubated in thepresence of the test compound and (ii) in the at least one partincubated in the absence of the test compound. The skilled person isaware of various methods available to count cells of a particularphenotype. In this respect, “phenotype” refers to an observablecharacteristic or trait of a cell. The phenotype results from theexpression of an organism's genetic code, its genotype, as well as theinfluence of environmental factors and the interactions between the two.Phenotypes of cells include but are not limited to a particular cellmorphology, size, both of the cell as a whole or of subcellular parts,cellular viability, expression of a protein, location of a particularprotein in a particular location, co-localization of proteins,post-translational modifications of proteins such as phosphorylation,nutrient uptake and consumtpion and others. A phenotype may also befunctional in nature in that a particular trait is only exhibited inresponse to a certain stimulus such as stimulation with a cytokine, apathogen or some other extracellular or intracellular stimulus.

In a preferred embodiment of the invention, the distinguishablephenotype in step (d) is viability and (i) if the selectivity determinedin step (e) is <1 the test compound is determined to selectively reducethe number of viable cells of the one sub-population of step (d), and(ii) if the selectivity determined in step (e) is >1 the test compoundis determined to selectively improve viability of the one sub-populationand/or to selectively reduce the viability of one or more of thesub-population(s) other than the one sub-population of step (d).

Subsequently, selectivity of the test compound(s) to induce thephenotype of the cells counted in the previous step as part of one ofthe sub-populations is determined. In the present invention, this isdone by dividing (i), as immediately above, through (ii), as immediatelyabove, wherein the test compound selectively induces the phenotypereferred to in (d) if (i) divided through (ii) is greater than 1,preferably greater than 1.05, 1.1, 1.5, 2, 3 most preferably 5, andselectively inhibits or reduces the phenotype referred to in (d) if itis less than 1, preferably less than 0.95, 0.9, 0.7, 0.5, 0.3, mostpreferably less than 0.2.

As shown in the appended Examples, the resulting selectivity of the testcompound(s) towards a target cell population is more robust towardsvariation of total cell numbers in different measurements carried out inthe course of the method, requires measurement at fewer concentrationsand takes into account the interplay of different cell populationscomprising a total population of cells.

In a further embodiment of the invention, a method for determiningwhether a subject suffering from cancer will respond or is responsive totreatment with a test compound is provided, wherein the method comprisesthe steps (a) providing a sample obtained from the subject comprising atleast two sub-populations of cells in a total population cells, whereinat least one sub-population corresponds to cancerous cells and at leastone sub-population corresponds to non-cancerous cells; (b) dividing thesample into at least two parts; (c) incubating at least one partobtained in step (b) in the absence of a test compound and at least onepart in the presence of a test compound; (d) determining the number ofviable cells in at least one of the sub-populations corresponding tocancer cells relative to the number of viable cells in the totalpopulation of cells in (i) the at least one part incubated in thepresence of the test compound and (ii) the at least one part incubatedin the absence of the test compound; and (e) determining whether thesubject will respond or is responsive to treatment with the testcompound by dividing (i) through (ii), wherein the subject will respondor is responsive to treatment if the resulting value is less than 1,preferably less than 0.95, 0.9, 0.8, 0.6, 0.4 most preferably less than0.2.

Accordingly, the invention provides for methods for use in a diagnosticmethod for determining whether a subject will respond or is responsiveto treatment with a test compound, in particular a therapeutic agent. Asdetailed above, a given test compound, in particular therapeutic agent,e.g. one of the therapeutic agents listed further above, may exhibit atherapeutic effect different for individual subjects suffering from thesame or similar disease, e.g. cancer. Therefore, it is advantageous todetermine the selectivity of a test compound, in particular therapeuticagent, individually for a given subject. In the above method of theinvention, selectivity of a test compound, in particular a therapeuticagent, may be determined in a highly reliable manner with an improvedprobability as compared to methods of the prior art that a testcompound, in particular therapeutic agent, that was determined to havean improved selectivity as compared to one or more alternative testcompound(s), in particular therapeutic agent(s), will exhibit anadvantageous effect in an in vivo context.

That is, analysis of the selectivity, using the methods provided herein,of a test compound towards a sub-population of cells within thesample/image is predictive of the response of the disease state to thetherapy tested in the donor; in this respect the methods of theinvention provide advantages over current methods available in the art.

In one embodiment, the method for determining whether a subjectsuffering from cancer will respond or is responsive to treatment with atest compound is repeated for at least two test compounds and whetherthe subject will respond or is responsive to treatment with acombination of the at least two test compounds is determined bysubtracting the values obtained in (e) for each of the at least two testcompounds from 1.0, and summing over the resulting values for the atleast two test compounds wherein if the resulting sum is greater than−1, preferably greater than −0.5, 0, 0.5, most preferably greater than1, the subject is determined to respond or be responsive to treatmentwith the combination of the at least two test compounds.

In one embodiment of the invention, the test compound used in themethods of the invention may comprise more than one chemical substance.That is, the present invention, in one embodiment, relates to themethods of the invention as disclosed herein, wherein the testcompound(s) comprise(s) one or more chemical substances. The presence ofmore than one chemical substance in the test compound used in themethods of the present invention may provide useful information withrespect to, for example, synergistic effects between the at least twochemical substances. That is, chemical substances may influence eachother with respect to their selectivity for a given target cell. Inorder to reliably determine said selectivity and/or in order to use thedetermined selectivity in the methods of the present invention, it isthus advantageous to use test compound(s) comprising more than onechemical substance.

In a further embodiment of the present invention, the at least one partobtained in step (b) of the methods of the present invention is furtherdivided into at least two parts, wherein each of the at least two partsis incubated with the test compound at different concentrations.Determining the selectivity of a test compound at differentconcentrations of the test compound and/or determining whether a subjectsuffering from cancer will respond or is responsive to treatment, with atest compound at different concentrations of the test compound mayprovide further improved results, because effective concentrations invivo may vary depending on dosage and timing of an administered testcompound. That is, in order to take potential effects associated withthe concentration of the test compound into account, the testcompound(s) may, in one embodiment of the invention, incubated with theat least two parts obtained in step (b) of the methods of the inventionat different concentrations. The skilled person is aware of typicalconcentrations used in methods known in the art to determine selectivityof a test compound. That is, concentrations will typically be between100 μM and 100 μM, preferably concentrations of 10 μM and 1 μM, morepreferably of 10 μM, 1 ρM and 100 nM are used.

In a preferred embodiment of the invention, in particular in the methodsof the present invention where a test compound is incubated at differentconcentrations with one or more part(s) obtained in step (b) of themethods of the invention, an average selectivity can be calculated instep (e) and used for determining the final selectivity. The averageselectivity may provide a more reliable measure that is even furtherimproved over selectivity determined by methods known in the art.

Similarly, in one embodiment of the invention, the methods of theinvention comprise in step (c) that at least two parts are incubated inthe absence of a test compound and/or at least two parts are incubatedin the presence of a test compound, and that in step (d) the averagenumber of cells in the one of the at least two sub-populations relativeto the number of cells in the total population of cells in (i) the atleast two parts incubated in the presence of the test compound and/or(ii) in the at least two parts incubated in the absence of the testcompound is determined. Averaging over multiple measurements reducespotential unwanted effects that may. occur in a single measurement dueto natural sample variation. That is, averaging may significantly reducethe expected error of obtained results and thus result in a morereliable outcome of the methods of the invention.

Accordingly, in one embodiment, the invention relates to a methodaccording to the invention, wherein at least one part obtained in step(b) is further divided into at least two parts, wherein each of the atleast two parts is incubated in step (c) with the test compound atdifferent concentrations and wherein steps (d) and (e) are repeated foreach concentration of the test compound independently to determine avalue at each concentration of the test compound whereby an averagevalue over all concentrations is calculated after step (e) and used fordetermining the final value.

In a further embodiment, the invention relates to a method according tothe invention, wherein in step (b) the sample is divided into at leastthree parts and in step (c) at least two parts are incubated in theabsence of a test compound and/or at least two parts are incubated inthe presence of a test compound whereby each part incubated in thepresence of the test compound is incubated in the presence of the sameconcentration of the test compound, and wherein in step (d) the numberof cells in the one of the at least two sub-populations that exhibit adistinguishable phenotype relative to the number of cells in the totalpopulation of cells that exhibit the same distinguishable phenotype isdetermined for (i) each part incubated in the presence of the testcompound independently and/or (ii) each part incubated in the absence ofthe test compound independently and the average of the relative numbersobtained in (i) and/or the average of the relative numbers obtained in(ii) is used.

In a further embodiment, the invention relates to a method according tothe invention, wherein in step (b) the sample is divided into at leastthree parts and in step (c) at least one part is incubated in theabsence of, a test compound and/or at least two parts are incubated inthe presence of at least two different concentrations of the testcompounds and in step (d) the number of cells in the one Of the at leasttwo sub-populations that exhibit a distinguishable phenotype relative tothe number of cells in the total population of cells that exhibit thesame distinguishable phenotype is determined for (i) each part incubatedin the presence of the test compound independently and/or (ii) each partincubated in the absence of the test compound independently wherein theaverage of (i) is determined for each concentration independently and/orthe average of (ii) is determined and used for further steps and whereinin step (e) the selectivity/value is determined for each concentrationof the test compound by dividing the average of (i) for eachconcentration through the average of (ii) and the finalselectivity/value is obtained by averaging the selectivity/value foreach concentration.

In a further embodiment, the invention relates to a method according tothe invention, wherein the method is repeated for at least two testcompounds and the test compound with the lowest value obtained in step(e) is selected for treatment of the subject suffering from cancer.

In a further embodiment, the invention relates to a method according tothe invention, wherein the method is repeated for at least three testcompounds and the combination of at least two of the at least three testcompounds with the highest value obtained by subtracting the valuesobtained in (e) for each of the at least two test compounds in thecombination from 1.0, and summing over the resulting values for the atleast two test compounds in the combination, is selected for treatmentof the subject suffering from cancer.

Accordingly, the invention also relates to a method for determiningwhich of several test compounds will most likely give the best clinicalbenefit to a patient suffering from cancer whereby the methods of theinvention are repeated for two or more test compounds and the testcompound with the lowest value as determined in step (e) of the methodsof the invention will be the test compound that most likely gives thepatient suffering from cancer the biggest clinical benefit. Thus, theinvention also relates to the use of the resulting test compound in thetreatment of cancer and the use of the test compound in the manufactureof a pharmaceutical composition for use in treating cancer.

In a further embodiment, the invention relates to a method fordetermining which of two or more distinct combinations of test compoundscomprising two or more test compounds each will most likely give thebiggest clinical benefit to a patient suffering from cancer whereby themethod according to the invention is repeated for the two or more testcompounds comprising the two or more distinct combinations of testcompounds each. The combination of the two or more test compounds withthe highest resulting sum obtained from subtracting the selectivityvalues obtained in (e) for each of the at least two test compoundscomprising the combination each from 1.0, and summing over the resultingvalues for the at least two test compounds is the combination of testcompounds that will most likely give the patient suffering from cancerthe highest clinical benefit. Thus, the invention also relates to theuse of the combination of test compounds for treating cancer.

As detailed above, the methods of the present invention may be used fordetermining selectivity of a test compound towards cells comprised in atotal population of cells, wherein the total population of cellscomprises at least two distinguishable subgroups of cells. In principle,any population of cells may be used in the methods of the presentinvention. However, it is preferred to use PBMCs or bone marrow cells.There are various diseases associated with cells comprised in a PBMC orbone marrow cell sample, in particular proliferative diseases such ascancer. Thus, in the methods of the present invention, in particular inthe methods for determining whether a subject suffering from cancer willrespond or is responsive to treatment with a test compound, the canceris preferably a cancer associated with PBMCs or bone marrow cells orcells derived from PBMCs or bone marrow cells. The skilled person isaware of cancerous diseases falling within this definition, i.e. typesof cancer associated with PBMCs or bone marrow cells or cells derivedfrom PBMCs or bone marrow cells. However, the methods of the presentinvention are not limited to cancer. That is, the methods of the presentinvention can be used to determine whether a subject will respond/isresponsive to treatment of the following diseases of the followingICD-10 codes (not limited thereto) A00-B99—certain infectious andparasitic diseases; C00-C97 —malignant neoplasms; D70-77—other diseasesof the blood forming system; D80-89—certain disorders involving theimmune mechanism, not classified elsewhere; D82—Immunodeficiencyassociated with other major defects; D83—Common variableimmunodeficiency; D84—Other immunodeficiency; G35-37—Diseases of thecentral nervous system; I00-I03—acute rheumatic fever; I05-I09—Chronicrheumatic heart disease; I01—Rheumatic fever with heart involvement;I06—Rheumatic aortic valve diseases; I09—Rheumatic myocarditis;I70—Atherosclerosis; K50—Crohn's disease; K51—Colitis; K52—othernoninfective gastroenteritis and colitis; M00-M19 Athropathies;M05—Seropositive rheumatoid arthritis; M06—Other rheumatoid arthritis;M10—Gout; M11—Other crystal athropathies; M35—sicca syndrome;M32—Systemic lupus erythematosus; N70-77—inflammatory diseases of femalepelvic organs; P35-39—infections specific to the perinatal period;P50-P61—hemorrhagic and hematological disorders of the fetus andnewborn; Z22—Carrier of infectious disease; Z23—Need for immunizationagainst single bacterial diseases; and/or Z24—Need for immunizationagainst certain single viral diseases.

In order to even more reliably determine the selectivity of a testcompound and/or determine whether a subject will respond/is responsiveto treatment, the methods of the present invention, in a preferredembodiment, make use of a sample that is a tissue sample that containsat least 1% cancerous cells and/or at least 1% non-cancerous cells. Morepreferably, the tissue sample contains at least 2% cancerous cellsand/or at least 2% non-cancerous cells, even more preferably at least 5%cancerous cells and/or at least 5% non-cancerous cells. Most preferably,the tissue samples contain at least 10% cancerous cells and/or at least10% non-cancerous cells.

As disclosed further above, it is preferred in the methods of thepresent invention that the sample, in particular the tissue sample, iscultured as a monolayer. In case the sample is derived from cellscontained in PBMCs or bone marrow which comprise non adherent cells, thetissue sample is preferably cultured as a non-adherent cell monolayer.The present invention thus provides methods using physiologicallyrelevant, multi-population cell samples, in particular primaryhematopoietic samples in imaging studies to determine in ahigh-throughput manner: 1) the effects of a test compound, for example atest compound to be used in chemotherapy/immunotherapy/immunesuppressive therapy on ex vivo cell population diagnostic, or other,markers at a global level based on single-cell analysis, 2) the abilityfor this technique to provide predictions as to which chemotherapy willbe beneficial for which patient based on ex vivo measurements in patientsamples, 3) the ability for this technique to determine the effect ofmany stimuli or a stimulus (e.g. drugs) on the immune function, and 4)for the integration of many patient data sets over time to determinepatterns in treatment assessments. In principle, any cell sample may beused in the methods of the present invention such as mononuclear cellsfrom blood, bone marrow, pleural effusion, spleen homogenates, lymphtissue homogenates, skin homogenates. However, it is preferred thatmononuclear cells are used. As the skilled person is aware, mononuclearcells samples as used in the methods of the invention comprise, interalia, PBMCs and bone-marrow cells, as well as others. Accordingly, thecell sample, preferably the monolayer of primary mononuclear cells asused in the methods of the invention may comprise PBMCs and/orbone-marrow cells. That is, while the methods provided herein aredescribed for cells in general or PBMCs, the skilled person understandsthat methods are provided for bone-marrow cells or further cells.Accordingly, provided herein are methods using bone-marrow cells,methods for determining selectivity of a test compound towards cellscomprised in a bone-marrow sample, and methods for determining whether asubject suffering from or predisposed to a disease will respond or isresponsive to treatment with a test compound comprising the use ofbone-marrow cells.

In this regard, bone marrow is the flexible tissue in the interior ofbones. In humans, red blood cells are produced by cores of bone marrowin the heads of long bones in a process known as hematopoiesis. Bonemarrow transplants can be conducted to treat severe diseases of the bonemarrow, including certain forms of cancer such as leukemia.Additionally, bone marrow stem cells have been successfully transformedinto functional neural cells and can also be used to treat illnessessuch as inflammatory bowel disease. Accordingly, bone-marrow cellsrepresent a valuable target in the treatment of various diseases, forexample cancerous diseases or inflammatory diseases such as inflammatorybowel disease. As such, the methods provided herein using bone-marrowsamples obtained from a donor are highly useful in theassessment/determination whether a donor suffers from such a disease oris predisposed to suffer from a disease. In addition, the methodsprovided herein using bone-marrow cells provide various advantages inhigh-throughput drug screening and the like.

The dogma of requiring adherent cells (macrophages, HeLa, etc.) to forma stainable and imageable monolayer has been overcome by the provisionof monolayers in WO 2016/046346. Prior to the monolayers as describedtherein, research groups have been unable to implement image-basedsingle cell screening techniques in primary patient samples forhigh-throughput determination of chemotherapy-induced molecular(biomarker) changes, cancerous blast viability assessments and cell-cellcontacts, in particular where the disease state is represented orreflected in non-adherent cells, e.g., in blood-based diseases orconditions such as lymphomas and leukemias. To solve this problem, theinventors of WO 2016/046346 have provided means and methods as well as amethodology and image-analysis pipeline, referenced herein as“pharmacoscopy”, which allows the visualization of adherent andnon-adherent cells in a single image, typically requiring only 1/10^(th)of the material needed per perturbation as compared to methods known inthe art, and maximizing throughput and speed. Pharmacoscopy can providethe same information gathered by known methods, e.g., flow cytometry,but provides additional advantageous information such as measurement ofsubcellular phenotypes (protein localization/co-localization) andcellular microenvironment/neighbor relationship. Moreover, the describedmethods of WO 2016/046346 require fewer cells and therefore less patientmaterial, less liquid volume, and nearly no human intervention;pharmacoscopy thereby greatly increases the number of molecularperturbations which can be tested in parallel and yields more detailedassessments. Moreover, without the need to sort diseased cells from theinherent healthy populations, pharmacoscopy can track drug mediatedphenotypic changes while controlling, in parallel, the off-target drugeffects. These important controls are done by relating test compoundeffects on target cells (e.g., cancerous cells) to total cells (e.g.healthy cells) from the same donor, present in the same well, and in thesame imaging field. The methods of the present invention use themethodology of WO 2016/046346, but comprise a further surprising andunexpected advantage. In particular, it is now possible to more reliablydetermine the selectivity of a test compound and/or determine whether asubject suffering from a disease, in particular cancer, will respond oris responsive to treatment with a test compound. This is achieved bytaking into account unspecific effects of the test compound onoff-target cells comprised in the sample representation, in particularthe monolayer.

Using the methods of the invention large numbers of test compounds canbe efficiently and quickly analyzed, i.e. their selectivity bedetermined, using the large numbers of monolayers that may be derivedfrom a single sample obtained from, for example, a patient/subject, inparticular a PBMC sample or bone-marrow sample. Typically, the effect ofat least 1000, at least 4000, at least 8000, at least 12000, at least16000, at least 20000, at least 24000, at least 50000, at least 75000,or up to 90000 test compounds or more can be investigated in themultiple monolayers obtained from such a single sample. In certainembodiments, the monolayers provided herein can be imaged and analyzedusing multiple channels simultaneously of high content data. The numberof channels of data available is dependent only on the particularimaging software and available staining methodologies, which fieldrapidly advances. Currently available methodologies allow thesimultaneous imaging, processing and analysis of at least two channels,and more typically, 4, 5 or 8 channels of high-content data.

In the methods of the present invention, the cells, preferably in theform of monolayers, may be imaged according to any methods known in theart and/or described herein and the methods provided herein may use anyimaging technique known in the art. The particular imaging method is notcritical and may be decided according to the knowledge of the person ofskill in the art. The imaging may or may not require the use of a dye orstain, may comprise imaging of both stained and non-stained componentsand/or may comprise imaging under conditions wherein the stain is or isnot visible (e.g., imaging in bright-field (wherein a fluorescent stainwould not be visible) and under UV-lighting (wherein a fluorescent stainwould be visible), or combinations thereof. Imaging under bright-fieldconditions is well known and routine used in the art, and may beperformed according to standard methods and/or as described herein.Additionally or alternatively, any other label-free imaging may be usedin accordance with the invention. Such label-free methods are known andinclude, e.g., PhaseFocus imaging (Phase Focus Ltd, Sheffield, UK).

In a preferred embodiment of the invention, the number of viablecancerous and non-cancerous cells is determined using automatedmicroscopy. In an even more preferred embodiment, the number of viablecells is determined as the number of non-fragmented nuclei. Methods todetermine the fragmentation of nuclei include but are not limited tostaining nuclei with DAPI, or dyes of the Hoechst series of nuclear dyesand assessing their morphology under fluorescence microscopy.

The practice of the invention may also comprise the addition of adetectable label to the cells, preferably the monolayer, in particularthe PBMC monolayer (either in connection with label-free methods orindependently), which label may be detected using microscopic methods inorder to selectively label cells of a particular phenotype such asviability and/or cells of a distinguishable sub-population. Thedetectable labels may label discrete cellular structures, components orproteins as known in the art. The label may also be attached toantibodies to specifically label and allow the detection of the antibodyantigen. In a preferred embodiment, the detectable label allowsvisualization of the label under visible or ultra-violet light. Thus thedetectable label may be fluorescent. A multitude of visual labels areknown in the art and are suitable for the invention. The labels may bedetectable without further action, or may only become detectable afterperformance of a secondary step, e.g., addition of a substrate, exposureto enzymatic reactions, or exposure to specific light wavelengths.

Cellular subpopulations, i.e. distinguishable subpopulations as usedherein, in particular PBMC subpopulations or bone-marrow cellsubpopulations may be identified by detectable labels via expression ofone or more markers on the surface of the target cell or inside of thecell. Alternatively or additionally, subpopulations may be defined bythe lack of expression of one or more markers on the surface of thetarget cell or inside the target cell. It may be desirable to test forexpression or lack of expression of one or more markers (e.g., twomarkers, three markers, four markers, etc.) to provide further assurancethat a cell expressing or not expressing a marker is in fact a targetcell, e.g., a member of desired subpopulation of cells. For example, a“cocktail” of antibodies to different markers may be each coupled(whether directly or indirectly) to the same label or to differentlabels. As an example, a cocktail of antibodies to different markers mayeach contain a binding motif that binds the same label (e.g., each maycontain an Fc of the same species that is recognized by the samesecondary antibody, or each may be biotinylated and specifically boundby the same avidin-coupled label). Optionally, two or more differentantibodies or cocktails of antibodies may be utilized. Preferably thecells are stained using at least two labels that can be distinguishedfrom one another, thereby permitting identification of cells thatexpress at least two different markers of the target cell types. Cellsmay also be stained using at least three, four, five, or more differentlabels that can be distinguished from one another, thereby permittingdetection of cells that express greater numbers of markers of the targetcell type. Optionally, a cell may be identified as a cell of the targettype if it expresses a preselected number of markers or certainpreselected combinations of markers or a cell may be identified as acell of the target type if it does not express a preselected marker.Additionally, it is not necessary that the marker(s) of the target celltype be unique to the target cells, as long as they permit distinctionof the target cells from other cells in the population. In the case ofPBMCs, major components of PBMC cell populations are represented byCD11C for dendritic cells, CD14 for macrophages, CD3 (CD4 or CD8 withCD3) for T-cells and CD19 for B-cells. While the foregoing markersoverlap on subsets of these major classes of PBMCs, staining with thesemarkers for identifying subpopulations of PBMCs is widely accepted inthe field. Further markers suitable for use in methods of the presentinvention may be found in the CD marker handbook (Becton, Dickinson andCo. 2010, CA, USA). Major cell subpopulations comprised in bone-marrowcells are neutrophilic metamyelocytes, neutrophilic myelocytes,segmented neutrophils, normoblasts and lymphocytes.

It is preferred to use antibodies conjugated to detectable labels in thepractice of the invention. Such antibodies allow the targeting ofdiscrete cellular structures and, thus, cocktails of such antibodies(each bearing a different label) may be used to simultaneously visualizemultiple targets/cellular structures/cellular components. Care must betaken during staining to avoid monolayer disruption. As the skilledperson appreciates, this is particularly problematic with the use ofantibody-based labels, as their use normally requires one or morewash-steps to eliminate unbound label that would interfere with accuratevisualization, i.e., would result in non-specific staining and/or assay“noise”. Accordingly, the invention encompasses methods for the stainingof cell monolayers with a detectable label, in particular, anantibody-based label, which minimizes or eliminates washing requirementssubsequent to staining. The methods of the invention may comprise addingthe detectable label(s) at concentrations that avoid generation of noisesignal in the absence of washing, which can be determined by methodswell known in the art and/or described herein. Thus, the inventionencompasses the use of labeled antibodies at concentrations above orbelow that recommended by the antibody manufacturers.

For some exemplary cell populations, cells may only be consideredpositive for a given marker if that marker exhibits a characteristiclocalization or pattern within the cell. For instance, a cell may beconsidered “positive” if a cytoskeletal marker is present in thecytoskeleton and “negative” if there is some diffuse cytoplasmicstaining. In such a case, cells may be cultured under suitableconditions (e.g., as adherent cultures) to establish the characteristiclocalization or pattern within the cell. Suitable culture conditions andtime for cytoskeleton assembly (or other processes to establishsubcellular organization) that may be necessary for robust detection ofa given marker are readily determined by those of ordinary skill in theart. Additionally, markers may readily be chosen which decrease oreliminate the need for adherent culture as a precondition to robuststaining.

Dyes useful in labeling proteins are known in the art. In general, a dyeis a molecule, compound, or substance that can provide an opticallydetectable signal, such as a colorimetric, luminescent, bioluminescent,chemiluminescent, phosphorescent, or fluorescent signal. In a preferredembodiment of the invention, the dye is a fluorescent dye. Non-limitingexamples of dyes, some of which are commercially available, include CFdyes (Biotium, Inc.), Alexa Fluor dyes (Invitrogen), DyLight dyes(Thermo Fisher), Cy dyes (GE Healthscience), IRDyes (Li-Cor Biosciences,Inc.), and HiLyte dyes (Anaspec, Inc.). In some embodiments, theexcitation and/or emission wavelengths of the dye are between 350 nm to900 nm, or between 400 nm to 700 nm, or between 450-650 nm.

For example, staining may comprise using multiple detectable labels,e.g. antibodies, self-antibodies or patient serum. A stain may beobservable under visible light and under ultraviolet light. A stain maycomprise an antibody directly or indirectly coupled to a colored reagentor an enzyme capable of producing a colored reagent. When antibodies areused as a component of a stain, a marker can be directly or indirectlycoupled to the antibody. Examples of indirect coupling includeavidin/biotin coupling, coupling via a secondary antibody, andcombinations thereof. For example, cells may be stained with a primaryantibody that binds a target-specific antigen, and a secondary antibodythat binds the primary antibody or a molecule coupled to the primaryantibody can be coupled to a detectable marker. Use of indirect couplingcan improve signal to noise ratio, for example by reducing backgroundbinding and/or providing signal amplification.

The stain may also comprise a primary or secondary antibody directly orindirectly coupled (as explained above) to a fluorescent label. Thefluorescent label may be selected from the group consisting of: AlexaFluor 350, Alexa Fluor 405, Alexa Fluor 430, Alexa Fluor 488, AlexaFluor 514, Alexa Fluor 532, Alexa Fluor 546, Alexa Fluor 555, AlexaFluor 568, Alexa Fluor 594, Alexa Fluor 610, Alexa Fluor 633, AlexaFluor 635, Alexa Fluor 647, Alexa Fluor 660, Alexa Fluor 680, AlexaFluor 700, Alexa Fluor 750 and Alexa Fluor 790, fluorosceinisothiocyanate (FITC), Texas Red, SYBR Green, DyLight Fluors, greenfluorescent protein (GFP), TRIT (tetramethyl rhodamine isothiol), NBD(7-nitrobenz-2-oxa-1,3-diazole), Texas Red dye, phthalic acid,terephthalic acid, isophthalic acid, cresyl fast violet, cresyl blueviolet, brilliant cresyl blue, para-aminobenzoic acid, erythrosine,biotin, digoxigenin, 5-carboxy-4′,5′-dichloro-2′,7′-dimethoxyfluorescein, TET (6-carboxy-2′,4,7,7′-tetrachlorofluorescein), HEX(6-carboxy-2′,4,4′,5′,7,′-hexachlorofluorescein), Joe(6-carboxy-4′,5′-dichloro-2′,7′-dimethoxyfluorescein)5-carboxy-2′,4′,5′,7′-tetrachlorofluorescein, 5-carboxyfluorescein,5-carboxy rhodamine, Tamra (tetramethylrhodamine), 6-carboxyrhodamine,Rox (carboxy-X-rhodamine), R6G (Rhodamine 6G), phthalocyanines,azomethines, cyanines (e.g. Cy3, Cy3.5, Cy5), xanthines,succinyifluoresceins, N,N-diethyl-4-(5′-azobenzotriazolyl)-phenylamine,aminoacridine, and quantum dots.

Further exemplary embodiments of the present method utilize antibodiesdirectly or indirectly coupled to a fluorescent molecule, such asethidium bromide, SYBR Green, fluorescein isothiocyanate (FITC), DyLightFluors, green fluorescent protein (GFP), TRIT (tetramethyl rhodamineisothiol), NBD (7-nitrobenz-2-oxa-1,3-diazole), Texas Red dye, phthalicacid, terephthalic acid, isophthalic acid, cresyl fast violet, cresylblue violet, brilliant cresyl blue, para-aminobenzoic acid, erythrosine,biotin, digoxigenin, 5-carboxy-4′,5′-dichloro-2′,7′-dimethoxyfluorescein, TET (6-carboxy-2′,4,7,7′-tetrachlorofluorescein), HEX(6-carboxy-2′,4,4′,5′,7,7′-hexachlorofluorescein), Joe (6-carboxy-4′,5′-dichloro-2′,7-dimethoxyfluorescein)5-carboxy-2′,4′,5′,7′-tetrachlorofluorescein, 5-carboxyfluorescein,5-carboxy rhodamine, Tamra (tetramethylrhodamine), 6-carboxyrhodarnine,Rox (carboxy-X-rhodamine), R6G (Rhodamine 6G), phthalocyanines,azomethines, cyanines (e.g. Cy3, Cy3.5, Cy5), xanthines,succinylfluoresceins, N,N-diethyl-4-(5′-azobenzotriazolyl)-phenylamineand aminoacridine. Other exemplary fluorescent molecules include quantumdots, which are described in the patent literature [see, for example,U.S. Pat. Nos. 6,207,299, 6,322,901, 6,576,291, 6,649,138 (surfacemodification methods in which mixed hydrophobic/hydrophilic polymertransfer agents are bound to the surface of the quantum dots), U.S. Pat.Nos. 6,682,596, 6,815,064 (for alloyed or mixed shells), each of whichpatents is incorporated by reference herein)], and in the technicalliterature [such as “Alternative Routes toward High Quality CdSeNanocrystals,” (Qu et al., Nano Lett., 1(6); 333-337 (2001)]. Quantumdots having various surface chemistries and fluorescence characteristicsare commercially available from Invitrogen Corporation, Eugene, Oreg.,Evident Technologies (Troy, N.Y.), and Quantum Dot Corporation (Hayward,Calif.), amongst others. Quantum dot” also includes alloyed quantumdots, such as ZnSSe, ZnSeTe, ZnSTe, CdSSe, CdSeTe, ScSTe, HgSSe, HgSeTe,HgSTe, ZnCdS, ZnCdSe, ZnCdTe, ZnHgS, ZnHgSe, ZnHgTe, CdHgS, CdHgSe,CdHgTe, ZnCdSSe, ZnHgSSe, ZnCdSeTe, ZnHgSeTe, CdHgSSe, CdHgSeTe, InGaAs,GaAlAs, and InGaN. Alloyed quantum dots and methods for making the sameare disclosed, for example, in US Application Publication No.2005/0012182 and PCT Publication WO 2005/001889.

Subsequent to labeling the cells used in the methods of the invention,preferably in the form of a monolayer, the method may further comprisedetecting the signal of the detectable label. Depending on the kind ofsignal emitted by the detectable label, the detection method may beappropriately adapted. It is preferred to use a detection methodsuitable for detecting fluorescent light emitting labels. The detectionmethod may also be automated according to standard methods known in theart. For example, various computational methods exist that enable aperson skilled in the art to analyze and interpret the microscopy imagesof cells or to establish automated protocols for their analysis. Forprimary image analysis, including the correction for illumination biasin microscopy images, the identification of individual cells frommicroscopy images and the measurement of marker intensities and texturesas well as nuclear and cellular size and shape and position parameters,the opensource software CellProfiler (e.g. version 2.1.1) can be used.Identification of marker-positive cells (such as CD34+ progenitor cellsor viability dye positive cells) can be performed by machine learningusing the opensource software CellProfiler Analyst (e.g. version 2.0)and double- or triple-positive cells can be identified by a sequentialgating strategy. Plate-overviews for further analysis and hit selectioncan be created using CellProfiler Analyst as well.

The cellHTS package in Bioconductor (e.g. version 2.14), or PipelinePilot (e.g. version 9.0; Accelrys), can both be used for the dataanalysis subsequent to the primary image analysis, includingplate-effect normalization, control-based normalization, and hitselection.

Commercial automated microscopy systems may also be used in the practiceof the invention, e.g., PerkinElmer Operetta automated microscope(PerkinElmer Technologies GmbH & Co. KG, Walluf, Germany), which systemsmay include corresponding image analysis software, e.g., PerkinElmer'sHarmony software (e.g. version 3.1.1). Such automated and/or commercialsystems can be used to perform primary image analysis, positive cellselection and hit selection from microscopic images according to themethods of the invention.

Subsequent to this primary analysis, the methods of the presentinvention are performed for determining the selectivity of a testcompound towards a cell population having a particular phenotypecomprised in a sample comprising at least two distinguishablesubpopulations of cells or for determining whether a subject sufferingfrom a disease, in particular cancer, will respond or is responsive totreatment with a test compound, wherein the method comprises thedetermination of the selectivity of a test compound based on its abilityto induce the phenotype above, in particular cell viability.

Based on the result of the method for determining whether a subjectsuffering from cancer will respond or is responsive to treatment with atest compound of the invention, a treatment decision may be taken, i.e.the test compound determined to have the most advantageous result withrespect to whether the subject will respond or is responsive totreatment with the test compound, may be chosen for treatment of thesubject.

When calculating the “mean” or “average” of numbers in the methods ofthe present invention, it is understood that this can refer to thearithmetic mean, the geometric mean and/or related statistical measuresthat have the aim to estimate a true value of a variable based onrepeated measurements associated with a random error. It is furtherunderstood by people skilled in the art that in some cases, it may beadvantageous to use the median instead of the mean (e.g., in cases whereoutliers are present but the underlying random variable is normallydistributed). In a preferred embodiment, the arithmetic mean is usedwhenever the methods of the present invention refer to “mean” or“average”.

When a test compound comprises more than one chemical substance, theconcentration of the test compound refers to a particular combination ofchemical substances at different concentrations and differentconcentrations of the test compound refer to at least one chemicalsubstance comprising the test compound having a different concentration.A test compound comprising more than one chemical substance having aparticular concentration means that all chemical substances comprisingthe test compound have one particular but not necessarily the sameconcentration.

“Treatment” or “treating” refers to both therapeutic treatment andprophylactic or preventative measures, wherein the object is to prevent,ameliorate or slow down (lessen) the targeted pathologic condition ordisorder, or one or more symptom associated therewith. Similarly,“responsive to” or “responds” and analogous terms refer to indicationsthat the targeted pathological condition, or one or more symptomassociated thereof, is prevented, ameliorated or lessened. The terms arealso used herein to denote delaying the onset of, inhibiting (e.g.reducing or arresting the growth of), alleviating the effects of, orprolonging, the life of a patient suffering from a disease, inparticular a myeloproliferative disease, or indications that suchmarkers have been accomplished. Those in need of treatment include thosediagnosed with the disorder, those suspected of having the disorder,those predisposed to have the disorder as well as those in whom thedisorder is to be prevented. Hence, the mammal to be treated herein mayhave been diagnosed as having the disorder or may be predisposed orsusceptible to the disorder.

“Response” or “responsive” refers to. a subject showing at least onealtered characteristic subsequent to treatment. The alteredcharacteristic of the subject may be amelioration or slowing down of thetargeted pathologic condition or disorder.

As used herein, the terms “prevent”, “preventing” and “prevention” referto the prevention of the occurrence and/or recurrence or onset of one ormore symptoms of a cancer disease in a subject resulting from theadministration of a prophylactic or therapeutic agent.

The means and methods provided herein are mostly described for primaryhematopoietic cells, or all monocyte cells. As the skilled personunderstands, primary hematopoietic cells comprise, inter alfa, PBMCs andbone-marrow cells. Accordingly, the means and methods provided herein,which are described for PBMCs, are also disclosed for bone-marrow cells,as well as any other mono-nucleated cell.

The test compound(s) used in the methods of the present invention may betherapeutic agent(s) used in the treatment/approved for treatment of adisease, in particular cancer. In this respect, “test compound” withinthe meaning of the invention are molecules including, withoutlimitation, polypeptides, peptides, glycoproteins, nucleic acids,synthetic and natural drugs, peptoides, polyenes, macrocyles,glycosides, terpenes, terpenoids, aliphatic and aromatic compounds, andtheir derivatives. In a preferred embodiment, the test compound is achemical compound such as a synthetic and natural drug. In anotherpreferred embodiment, the test compound effects amelioration and/or cureof a disease, disorder, pathology, and/or the symptoms associatedtherewith. The polymers may encapsulate one or more test compounds to beused in the methods of the invention.

As detailed immediately above, test compounds may also be selected fromknown therapeutic agents. In this respect, suitable therapeutic agentsinclude, without limitation, those presented in Goodman and Oilman's ThePharmacological Basis of Therapeutics (e.g., 9th Ed.) or The Merck Index(e.g., 12th Ed.). Genera of therapeutic agents include, withoutlimitation, drugs that influence inflammatory responses, drugs thataffect the composition of body fluids, drugs affecting electrolytemetabolism, chemotherapeutic agents (e.g., for hyperproliferativediseases, particularly cancer, for parasitic infections, and formicrobial diseases), antineoplastic agents, immunosuppressive agents,drugs affecting the blood and blood-forming organs, hormones and hormoneantagonists, vitamins and nutrients, vaccines, oligonucleotides and genetherapies. It will be understood that compositions comprisingcombinations, e.g. mixtures or blends of two or more active agents, suchas two drugs, are also encompassed by the invention.

In one embodiment the therapeutic agent may be a drug or prodrug,antibody or vaccine. The method of the invention may be used to assesswhether administration of a therapeutic agent to a patient triggers aresponse to the therapeutic agent, or a component of a delivery vehicle,excipient, carrier etc. administered with the therapeutic agent.

The precise nature of the therapeutic agent is not limiting to theinvention. In non-limiting embodiments the method of the invention maybe used to assess response to synthetic small molecules, naturallyoccurring substances, naturally occurring or synthetically producedbiological agents, or any combination of two or more of the foregoing,optionally in combination with excipients, carriers or deliveryvehicles.

The viability of cells comprised in the sample to be analyzed, inparticular in the monolayers can be determined/assessed/verified usingmethods well-known in the art. That is, the skilled person is well-awareof methods how to determine/assess/verify the stadium of a cell, forexample whether a cell is viable, live, dead or undergoing a processchanging its stadium, for example dying as in apoptosis or necrosis.Accordingly, known markers/dyes that specifically recognize/label cellsbeing in a particular stadium can be used in the methods of theinvention. That includes dyes/labels that are selective for cells withnon-intact membranes or dyes/labels selective for late-stage cell deathor early apoptosis. For example, fixable live/dead green can be used(ThermoFisher, catalogue number L-23101), antibodies against cytochromeC, determining DNA turnover or cell proliferation through the use ofdyes. Further means and methods how to determine/assess/verify viabilityof cells comprised in cell sample used in the present invention, inparticular in the form of a monolayer are known to the skilled person.

Determining/tracking/assessing/verifying changes of viability and/orcell-cell interactions of the two or more distinguishablesubpopulation(s) comprised in the cell sample, in particular themonolayer, in particular PBMC monolayer or bone-marrow cell monolayer,can be done using methods well-known in the art. For example, usingmicroscopy, changes can be determined/tracked/assessed/verified byoptical perception. However, for high-throughput applications, it ispreferred that an automated method is used, whichdetermines/tracks/assesses/verifies changes of viability and/orcell-cell interactions of individual subpopulations comprised in themonolayers. Such a method comprises identifying subpopulations comprisedin the cell sample, preferably the monolayer, e.g. by detectable labels.It can then be determined whether labeled/detected subpopulations showcell-cell interactions, wherein cell-cell interactions may includedirect contacts via plasma membranes (as described above) or indirectcontacts. Accordingly, a distance parameter, i.e. the threshold definedabove, between labeled cells is introduced, which determines the totalnumber of interactions, i.e. how many cell-cell interactions areobserved between labeled cells. In this procedure, a labeled cell of adistinguishable subgroup may interact with one or more cells of thesecond distinguishable subgroup, each interaction being counted. Theresulting number is compared to what would be expected by a randomdistribution function, i.e. by random cell-cell interactions. Theinteraction propensity can then be calculated using the methods of theinvention, i.e. an interaction score, which determines whetherinteraction is random or directed. Following such a protocol before andafter one or more test substance(s) are added to the cell sample of theinvention, allows determining/tracking/assessing/verifying changes ofcell-cell interactions due to the one or more test compound(s).

Unless otherwise defined, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which this invention pertains. Although methods and materialssimilar or equivalent to those described herein can be used in thepractice or testing of the present invention, suitable methods andmaterials are described below. In case of conflict, the presentspecification, including definitions, will control. In addition, thematerials, methods, and examples are illustrative only and not intendedto be limiting.

The general methods and techniques described herein may be performedaccording to conventional methods well known in the art and as describedin various general and more specific references that are cited anddiscussed throughout the present specification unless otherwiseindicated. See, e.g., Sambrook et al., Molecular Cloning: A LaboratoryManual, 2d ed., Cold Spring Harbor Laboratory Press, Cold Spring Harbor,N.Y. (1989) and Ausubel et al., Current Protocols in Molecular Biology,Greene Publishing Associates (1992), and Harlow and Lane Antibodies: ALaboratory Manual, Cold Spring Harbor Laboratory Press, Cold SpringHarbor, N.Y. (1990).

While aspects of the invention are illustrated and described in detailin the drawings and foregoing description, such illustration anddescription are to be considered illustrative or exemplary and notrestrictive. It will be understood that changes and modifications may bemade by those of ordinary skill within the scope and spirit of thefollowing claims. In particular, the present invention covers furtherembodiments with any combination of features from different embodimentsdescribed above and below.

The invention also covers all further features shown in the figuresindividually, although they may not have been described in the previousor following description. Also, single alternatives of the embodimentsdescribed in the figures and the description and single alternatives offeatures thereof can be disclaimed from the subject matter of the otheraspect of the invention;

Furthermore, in the claims the word “comprising” does not exclude otherelements or steps, and the indefinite article “a” or “an” does notexclude a plurality. A single unit may fulfil the functions of severalfeatures recited in the claims. The terms “essentially”, “about”,“approximately” and the like in connection with an attribute or a valueparticularly also define exactly the attribute or exactly the value,respectively. Any reference signs in the claims should not be construedas limiting the scope.

The patent or application file contains at least one drawing executed incolor. Copies of this patent or patent application publication with,color drawing(s) will be provided by the Office upon request and paymentof the necessary fee.

The present invention is also illustrated in some aspects by thefollowing figures.

FIG. 1: A. Two hypothetical dose response curves showing viability ofcancerous A cells and non-cancerous B cells as a function of drugconcentration of a cytotoxic test compound. B. Showing total cellviability and the fraction of viable A cells of viable total cells as afunction of test compound concentration. Here, when total cell viabilitygoes below 5% of the starting value, the fraction of viable A cells wasset to 0.8 (i.e., the fraction at zero test compound concentration) dueto the fact that quantifying small number of cells is associated withlarge errors. Following this approach, a selectivity of 1 will reliablybe assigned to test compounds with strong overall cytotoxicity whenfollowing the steps of the methods of the present invention.

FIG. 2: A. Selectivity/value of a cytotoxic test compounds to killcancer cells determined as described in the present invention as afunction of the difference of log EC50 of the test compound againstcancer A cells and non-cancerous B cells measuring at threeconcentration points (c.f., FIG. 1B). B. Selectivity/value determined asdescribed in the present invention as a function of the difference oflog EC50 of the test compound towards cancer cells and non-cancerouscells measuring at 400 concentration points. Already measurement atthree concentration points is sufficient to obtain selectivityinformation using the present invention. However, the more concentrationpoints, the more accurate the selectivity/value reflects the differencein log EC50.

FIG. 3: Selectivities/values of daunorucibin to kill AML blast cellsdefined as either being CD34+, CD117+ or CD34+/CD117+ determined forindividual daunorubicin concentrations using the present inventiondisplayed as a function of daunorucibin concentration. Patientsresponding to daunorucibin containing therapy had a lowerselectivity/value determined using the present invention than patientsnot responding to daunorubicin based 3+5+7 induction therapy acrossdifferent daunorubicin concentrations.

FIG. 4: Top panel: Selectivity/value of combinations ofdaunorubicin+cytarabine+etoposide to kill cancer cells (here defined asCD34 or CD117 expressing cells) in bone marrow samples of AML patientsdetermined according the present invention for responders andnon-responders to “3+5+7” induction therapy consisting of the threeaforementioned drugs. A cut off of 0.92 allows for classification ofpatients into responders and non-responders with a total classificationaccuracy of 0.85. Middle panel: Number of cancerous cells relative tonumber of cancerous cells at zero drug concentration averaged over alldrug concentrations and combinations. This metric only allowsclassification of patients into responders and non-responders with atotal classification accuracy of 0.65. Bottom panel: In analogy tomiddle panel but based on the total cell number. Accurate classificationis not possible using this metric.

FIG. 5: The area under the receiver operator curve was highest(AUROC=0.97) when predicting response of AML patients to daunorubicincontaining 3+5+7 induction therapy based on the selectivity ofdaunorubicin to kill AML blasts determined according to the presentinvention and using the approach described in Example 4 for downstreamdata processing. This demonstrates that measuring killingselectivity/value according to the present invention is advantageouscompared to e.g., basing the prediction of response on the number ofcancerous cells (AUROC=0.91). AML blasts are here defined as in FIG. 2.

FIG. 6: Left: Hematological cancer patients were treated withcombinations of 2 or more FDA approved drugs. For each patient thecombined selectivity was calculated as the sum of 1 minus the individualselectivites of the drugs given to the patient as determined accordingto the present invention. The combined selectivity was plot against theresponse (PD=progressive disease, SD=stable disease, PR=partialremission, CR=complete remission) and correlates with the response.Based on the integrated selectivity, patients could be classified intoresponders (CR and PR) and non-responders (PD and SD) with 92% accuracyand an AUROC of 0.84.

FIG. 7: Selectivities/values of FDA approved drugs to kill CD20+ cellsover CD20− cells of a diffuse large B-cell lymphoma patient determinedaccording to the present invention. The patient responded to treatmentwith ibrutinib.

FIG. 8: Selectivities/values of FDA approved drugs to kill CD20+ cellsover CD20− cells of a B-cell lymphoblastic lymphoma patient determinedaccording to the present invention. The patient responded to treatmentwith a combination of bortezomib and 6-mercaptopurine.

FIG. 9: Selectivities/values of FDA approved drugs to kill CD79a+ cellsover CD79a− cells of a diffuse large B-cell lymphoma patient determinedaccording to the present invention. The patient responded to treatmentwith a combination of bortezomib, cladribine and dexamethasone.

FIG. 10: The viability of cells of population A and population B aftertreatment with compound X at different concentrations [X] (log EC50towards A=−2 and log EC50 towards B=3 on an arbitrar concentrationscale) was calculated. Accordingly, the number of live cells ofpopulation A as a fraction of total live cells (population A+B) wasdetermined as Aviable/(Aviable+Bviable). A logistic dose response curvewas fit to the sigmoidal curve resulting from Aviable/(Aviable+Bviable)as a function of the concentration [X] (black line) and the log EC50determined as the inflection point. Neither log EC50A nor log EC50Bcorrespond to the log EC50 obtained from curve fitting (i.e., the logEC50 of the black line sigmoidal curve) demonstrating that a viabilityEC50A or EC50B cannot be obtained from fitting a logistic curve toAviable/(Aviable+Bviable).

EXAMPLES Example 1

Synthetic data simulating the response of a mixture of cells comprisedof cell population A and B to a cytotoxic drug X was provided. Xaffected A with a log EC50 of EC50A (e.g., 2.5 for FIG. 1A) and B with alog EC50B (e.g., 3 for FIG. 1B) on an arbitrary concentration scale.Based on these parameters, the number of live cells and total number ofcells of each type in the mixture of A and B cells could be calculatedassuming a standard 4-parameter logistic (i.e., sigmoidal),dose-response curve. At a concentration of [X]=0, a total number of10,000 cells at a ratio of A:B=0.8:0.2 was assumed. A measurement of theselectivity of X to kill A over B of a total number of only 3 drugconcentrations was simulated.

Drug selectivity was calculated using the present invention. Inparticular, for each measured drug concentration the number of viable Acells and the number of viable B cells was calculated. According to step(d) of the methods of the invention (i) the number of viable cells inone of the at least two sub-populations (here A) that exhibit adistinguishable phenotype (here: viability), relative to the number ofcells in the total population of cells (here viable A+viable B) thatexhibit the same phenotype in the presence of X at three differentconcentrations as Rx=Ax/(Ax+Bx) where Ax and Bx denote the number oflive A and B cells at three different concentrations [X] and (ii) for aconcentration of [X]=0 giving R0=A0/(A0+B0) was determined. Then, theselectivity at each concentration of [X] as Sx=Rx/R0 was determined andaveraged over all Sx to get the final selectivity ofSfinal=(S1+S2+S3)/3.

When determining the drug selectivity for different pairs of EC50A andEC50B using the present invention, surprisingly, it was linearlyproportional to the difference in log EC50 of X towards A and the logEC50 of X towards B (FIG. 2).

Example 2

Mononuclear cells were extracted from 20 bone marrow samples oftreatment naïve patients newly diagnosed with acute myeloid leukemia(AML) using Ficoll density gradient centrifugation. After bone marrowsamples had been taken, all 20 patients had undergone treatment withdaunorucibin, etoposide and cytarabine according to the “3+5+7” schedulewhereby 10 patients responded and 10 did not.

The mononuclear cells were suspended in RPMI+10%FCS+penicillin/streptomycin and were seeded into Perkin Elmer CellCarrier 384-well cell culture plates at a concentration 20,000 cells in50 μL medium per well whereby the wells had previously been loaded withcombinations of cytarabine, daunorubicin and etoposide at differentconcentrations. All possible drug and concentration combinations wererepresented on the plate with cytarabine taking concentrations of 0, 1,3, 10 and 20 μM, daunorubicin taking concentration of 0, 0.1, 1, 3 and10 μM and etoposide taking concentrations of 0, 1, 3, 10 and 20 μM thusgiving a 3-dimension drug titration matrix. Cells were allowed to formmonolayers according to WO 2016/046346 and monolayers were incubated for18 h, fixed by addition of 15 μL 4% formaldehyde solution in PBScontaining 0.5% Tritox X114, flicked and stained with DAPI as wellfluorescently labelled antibodies to mark CD34 and CD117 positive cells.After 1 h of incubation, images of each well were taken using an OperaPhenix automated confocal microscope (Perkin Elmer).

Marker positive cells were considered cancerous cells and markernegative cells as non-cancerous cells. The total number of live cellswas quantified by counting intact DAPI-stained nuclei using theCellProfiler computational image analysis software whereas fragmentednuclei were discarded as dead or dying. Similarly, the number of livecancerous cells was determined as antibody stained cells with intactDAPI-stained nuclei.

The selectivity of each drug to kill the cancerous populations wasdetermined according to the present invention by taking the fraction oflive cancerous cells of live total cells relative to the fraction oflive cancerous cells of live total cells in control wells (no drugs,just DMSO) for different concentrations of daunorubicin only (FIG. 3).Surprisingly, this measure alone could separate responders andnon-responders.

To take into account the contribution of all drugs, the selectivity ofeach drug to kill the cancerous populations was determined according tothe present invention by taking the fraction of live cancerous cells oflive total cells at each drug combination and concentration relative tothe fraction of live cancerous cells of live total cells in controlwells (no drugs, just DMSO) and averaging over all concentrations andcombinations of drugs. Using a cut-off value of 0.92, patients whoclinically responded to the drug combination could be distinguished frompatients who did not (FIG. 4, top panel) with a total classificationaccuracy of 0.85.

Example 3

In analogy to Example 2, if drug response was determined only based onthe sensitivity of cancer cells (here: CD34 or CD117 positive cells) orthe sensitivity of the total cell population, a classification accuracyof 0.65 or less was obtained (FIG. 4, middle and bottom panels,respectively).

Example 4

In analogy to Examples 2 and 3, this example illustrates how theselectivity determined according to the present invention can be used indownstream analysis to obtain a drug response score that allows for evenmore accurate classification of patients into responders andnon-responders. For each patient sample and combination of drugs atdifferent concentrations, the selectivity was calculated according tothe present invention and averaged at each concentration point overresponders and non-responders. The resulting data points span doseresponse surfaces in a four-dimensional dose-response space giving onesurface for responders and one surface non-responders. The surfaceoptimally separating the two dose response surfaces was determined bydetermining the cut-off point at each point in dose-response space thatallowed for optimal classification into responders and non-responders atthat particular drug dose combination. A response score was calculatedfor each patient by assigning a 1 to each point in dose response space,that was on the responders' side of the separating surface and a −1 thatwas on the opposite side. Summing over these indictors weighted by thetotal classification accuracy at each point in concentration spaceresulted in a final drug response score. This response score, forexample, allowed AML patients receiving 3+5+7 induction therapy to beseparated into responders and non-responders with over 90% totalclassification accuracy (FIG. 5) and area under the receiver operatorcurve (AUROC) of 0.97 whereas basing the same model on the number ofcancerous cells normalized to the number of cancerous cells at zero drugconcentration only, gave an AUROC of only 0.91 and basing it on cellnumber gave an AUROC of 0.86.

Example 5

Bone marrow aspirates, peripheral blood, pleural effusion, ascites, orexcised lymph node samples comprised of cells typically found in PBMCsor bone marrow were purified over Ficoll gradient (bone marrow,peripheral blood, pleural effusion, ascites) (GE healthcare) orhomogenized and filtered (lymph tissue) and resuspended in RPMI+10% FCSand penicillin/streptomycin. The resulting single-cell suspensions ofmononuclear cells commonly found in PBMCs were seeded in 384-well PerkinElmer Cell Carrier imaging plates at a concentration of 20,000 cells in50 μL medium per well plates according to WO 2016/046346 to formnon-adherent monolayers. Plates had previously been loaded with 140different clinically used anticancer drugs in 50 nL DMSO or 50 nL ofDMSO as control such that each drug after addition of 50 μL medium andcells was present at 1 or 10 μM final concentration in at least 3technical replicates per drug and concentration and the DMSOconcentration amounted to 0.1% v/v.

Monolayers were incubated overnight (18 h). Biopsies used for the studywere all freshly acquired and not stored frozen. Immunofluorescencestaining, imaging by automated microscopy (Opera Phenix, Perkin Elmer),image analysis (CellProfiler), and data analysis (Matlab) were performedas described previously in Vladimer et al Nat Chem Biol 2017. Theantibodies used to identify the target cancerous cell populations wereselected based on clinical pathology reports and antibody reactivityassessment, and included CD3 (HIT3a), CD19 (HIB19), CD20 (2H7), CD79a(HM47), CD34 (4H11), CD117 (104ED2), and CD138 (DL-101) fromeBiosciences. Unstained cells were considered non-cancerous cells.

The selectivity of drugs to kill cancer cells over non-cancerous cellswas determined according to the present invention by taking the averagefraction of live cancerous cells of live total cells for each drug andconcentration relative to the average fraction of live cancerous cellsof live total cells in control wells (no drugs, just DMSO). Thesequotients of average fractions over the two concentrations for each drugwere determined.

Patients treated with drugs that displayed a value/selectivity of <1 asdetermined according to the present invention had a higher chance ofresponding (i.e., achieving a complete or partial remission) thanpatients treated with drugs that were chosen without taking the value asdetermined according to the present invention into account or drugs thathad a value/selectivity of >1 as determined according to the presentinvention.

Moreover, when combinations of drugs were given to patients, the higherthe sum of one minus the individual value (FIG. 6) of the drugs given tothe patient, the higher the chance that the patient would respond.

Example 6

A 69-year-old man with Diffuse Large B-cell lymphoma (DLBCL) relapsedafter seven lines of prior treatment. Lymphoma cells of the sample wereresistant to most of the 104 drugs tested as indicated by a selectivityof >1 of the drugs to kill the cancerous cells relative to non-cancerouscells as determined according the present invention, while only sixcompounds displayed significant on-target effects ex vivo (FIG. 7).Cisplatin and oxaliplatin were not considered feasible given thepatient's history, age, and comorbidities, however the BTK inhibitoribrutinib showed the second strongest ex vivo efficacy(value/selectivity according to the present invention=0.61, P<0.00048;FIG. 7). A PET-CT performed on day 49 of ibrutinib treatment confirmed acomplete remission for the patient.

Example 7

A 51-year-old women with precursor B-cell lymphoblastic lymphoma (B-LBL)had undergone three lines of prior treatment, and was progressive afterimmunotherapy with the bi-specific CD3-CD19 antibody blinatumomab. Acell mixture comprising cells typically found in PBMCs was isolatedfrom, the woman's pleural effusion. The ability of 266 compounds toselectively kill cancerous versus non-cancerous cells contained in thecell mixture was determined using the present invention. It revealedthat the proteasome inhibitor bortezomib was able to selectively killcancer cancer cells (selectivity determined according to the presentinvention=0.50, P<0.001; FIG. 8) and the thiopurine 6-mercaptopurine,6-MP (value/selectivity determined according to the presentinvention=0.58, P<0.001; FIG. 8). 6-MP and bortezomib were combined withanti-CD20 obinutuzumab. After 28 days PET-CT confirmed a partialresponse.

Example 8

An excised lymph node of a patient with diffuse large B-cell lymphomawas dissociated into single cells giving a complex cell mixturecomprising cells typically found in PBMCs. The ability of 266 compoundsto selectively kill cancerous versus non-cancerous cells contained inthe cell mixture according to the present invention. The patientachieved a complete remission (FIG. 9) to a combination of the singlestrongest ex vivo acting drug, bortezomib (selectivity=0.59, P<0.0001;),with cladribine (selectivity=0.73; P<0.0003) and dexamethasone(value/selectivity=0.87; P<0.05; FIG. 9).

Example 9

This example describes the practical application of the methodsdescribed in claims (1) and following and in particular of claims 1) and(2). A tissue sample of a blood cancer patient comprised of 40,000 cellsis provided. 20,000 cells are cancerous cells and stain positive for thecell surface marker CD19. The remaining cells stain positive for othercell surface markers including CD3, 4, 8, 11c, 14, 56 and others. Thesample is divided into two parts of 20,000 cells each. The first sampleis incubated in RPMI+10% FCS in the presence of 10 μM bortezomib in DMSO(0.1% final DMSO concentration) whereas the second sample is incubatedin RPMI+10% FCS+0.1% DMSO. After 24 h incubation the viability of eachcell in each sample is determined whereby viability here is the“distinguishable phenotype” referred to in step (d) of claim 1 anddependent claims. In the bortezomib treated sample, 5,000 viable cellsstaining for CD19 are found and 10,000 viable cells negative for CD19stain are found. In the DMSO treated sample 10,000 viable cells stainingpositive for CD19 and staining negative for CD19 are found each.According to the present invention, the selectivity of bortezomib toreduce viability of the CD19 positive cells is calculated. Followingstep (d) the number of cells in one of the at least two sub-populations(here: CD19 positive cells) that exhibit a distinguishable phenotype(here: viability), relative to the number of cells in the totalpopulation of cells (CD19 positive+CD19 negative cells) that exhibit thesame phenotype (i.e., viability) in (i) the at least one part incubatedin the presence of bortezomib as the test compound (here:5,000/15,000=0.33) and (ii) in the at least one part incubated in theabsence of the test compound (here: 10,000/20,000=0.5) is calculated.

Following step (e) the selectivity of the test compound (here:bortezomib) to induce the phenotype referred to in (d) in the one subpopulation referred to in step (d) (here: CD19 positive cells) over allother subpopulations is determined by dividing (i) (here: 0.33) through(ii) (here: 0.50). Since 0.33/0.50=0.66 i.e., less than 1, the testcompound (here: bortezomib) selectively inhibits the phenotype of steps(d) (here: viability) in the one population explicitly referred to instep (d) (here: CD19 positive cells). So, according to the presentinvention we can conclude that bortezomib selectively reduced theviability of CD19 positive cells in the given example.

Example 10

This example describes a further practical application of the methods ofthe invention. A tissue sample of a blood cancer patient comprised of60,000 cells is provided. 30,000 cells are cancerous cells and stainpositive for the cell surface marker CD79a. The remaining cells stainpositive for other cell surface markers including CD3, 4, 8, 11c, 14, 56and others. Suitably labelled antibodies are used as staining reagents.

The sample is divided into two parts of 40,000 cells and 20,000 cells.The first part of 40,000 cells is further divided into two parts of20,000 cells each here denoted [1a] and [1b]. Parts [1a] and [1b] areincubated in RPMI+10% FCS in the presence of 10 μM and 1 μM bortezomibin DMSO (0.1% final DMSO concentration) respectively whereas the secondsample is incubated in RPMI+10% FCS+0.1% DMSO. CD79a here is only chosenas a hypothetical example for the sake of clarity and can be replacedwith any other surface marker.

After 24 h incubation the viability of each cell in each sample isdetermined whereby viability here is the “distinguishable phenotype” asused in the present invention. In the bortezomib treated sample [1a],5,000 viable cells staining for CD79a are found and 10,000 viable cellsnegative for CD79a stain are found. In the bortezomib treated sample[1b], 8,000 viable cells staining for CD79a are found and 10,000 viablecells negative for CD79a stain are found. In the DMSO treated sample10,000 viable cells staining positive for CD79a and staining negativefor CD79a are found each. The selectivity of bortezomib to reduceviability of the CD79a positive cells is calculated according to themethods of the invention.

For both parts [1a] and [1b] the number of, cells in the one of the atleast two sub-populations (here: CD79a positive cells) that exhibit adistinguishable phenotype (here: viability), relative to the number ofcells in the total population of cells (CD79a positive+CD79a negativecells) that exhibit the same phenotype (i.e., viability) in (i) the atleast one part incubated in the presence of bortezomib at the respectiveconcentration as the test compound (here: 5,000/15,000=0.33 for [1a] and8,000/18,000=0.44 for [1b]) and (ii) in the at least one part incubatedin the absence of the test compound (here: 10,000/20,000=0.5) iscalculated.

Following step (e) the selectivity of the test compound (here:bortezomib) to induce the phenotype referred to in (d) in the onesub-population referred to in step (d) (here: CD79a positive cells) overall other subpopulations is determined by dividing (i) (here: 0.33 for[1a] and 0.44 for [1b]) through (ii) (here: 0.50) and the averageselectivity is calculated as the final value/selectivity as(0.33/0.50+0.44/0.50)/2=0.77. Since 0.77 is less than 1, the testcompound (here: bortezomib) selectively inhibits the phenotype of steps(d) (here: viability) in the one population explicitly referred to instep (d) (here: CD79 positive cells). So, according to the presentinvention it can be concluded that bortezomib selectively reduced theviability of CD79a positive cells in the given example.

The patient from wham the sample was derived would respond to treatmentwith bortezomib. CD79a here is only chosen as a hypothetical example forthe sake of clarity and can be replaced with any other surface marker.Also cell numbers are only chosen arbitrarily for illustrative purposes.

Example 11

A tissue sample of a blood cancer patient comprised of 60,000 cells isprovided. 30,000 cells are cancerous cells and stain positive for thecell surface marker CD20. The remaining cells stain positive for othercell surface markers including CD3, 4, 8, 11c, 14, 56 and others.Suitably labelled antibodies are used as staining reagents. The sampleis divided into three parts of 20,000 cells each. Two parts of 20,000each are incubated in RPMI+10% FCS in the presence of 10 μM bortezomibin DMSO (0.1% final DMSO concentration) respectively whereas the thirdpart is incubated in RPMI+10% FCS+0.1% DMSO. Please note that CD20a hereis only chosen as a hypothetical example for the sake of clarity and canbe replaced with any other surface marker.

After 24 h incubation the viability of each cell in each sample isdetermined whereby viability here is the “distinguishable phenotype”. Inthe two samples treated with 10 μM bortezomib, 5,000 viable cellsstaining for CD20a are found and 10,000 viable cells negative for CD20astain are found each. In the DMSO treated sample 10,000 viable cellsstaining positive for CD20 and staining negative for CD20 are foundeach. The selectivity of bortezomib to reduce viability of the CD79apositive cells is determined. For both parts incubated in the presenceof 10 μM bortezomib the number of cells in the one of the at least twosub-populations, (here: CD20 positive cells) that exhibit adistinguishable phenotype (here: viability), relative to the number ofcells in the total population of cells (CD20 positive+CD20 negativecells) that exhibit the same phenotype (i.e., viability) in (i) eachpart incubated in the presence of bortezomib is calculated independently(i.e., 5,000/15,000=0.33 and 5,000/15,000=0.33) and (ii) for each partincubated in the absence of the test compound (here: 10,000/20,000=0.5)is determined independently. Then the average of (i) and (ii) are formedgiving 0.33 for (i) and 0.5 for (ii) and used for further steps, thatis, in step (e) the value/selectivity is determined by dividing theaverage of (i) by the average of (ii) giving 0.33/0.5=0.66 as the finalvalue/selectivity.

Example 12

This example illustrates that accurate EC50 values cannot be obtainedfrom fitting dose response curves to fractions of cells exhibiting aphenotype of total cells exhibiting the same phenotype. A mixture ofcells of type A and B at a ratio of A:B=0.2:0.8 was assumed. The cellmixture was treated with a cytotoxic compound X. The ability of compoundX to kill A cells was quantified with a log EC50 of 3 and the ability ofcompound X to kill B cells was quantified with a log EC50 of −2 on anarbitrary concentration scale. Calculating the fraction of the numberlive A cells of the total number of live cells (i.e. live A+live B), thesigmoidal curve shown in FIG. 10 was obtained. It can be clearly seen,that the inflection point of this curve (solid line) is neitherinformative of the EC50 of the dose response curve of X action on A norof X action on B.

Example 13

This example illustrates the effect of a 10% standard deviation in totalcell numbers when introducing a cell mixture of A and B cells into amicrotiter plate for determining selectivity of a test compound X tokill A over B cells. When determining the selectivity using the classicapproach of measuring total number of A and B cells as a function ofconcentration [X], to fit sigmoidal dose response curves and measure theEC50 of X towards A and B, each measurement point will have a standarddeviation of 10%. Using the present invention, a 10% variation in totalcell number will have no effect on the fraction of viable A cells of thetotal number of viable cells. The present invention thus allows for thedetermination of selectivity that is more robust towards variation inseeding of cells into assay plates or loss of cells during manipulation.

1. A method for determining the selectivity of a test compound, themethod comprising the steps: (a) providing a sample comprising at leasttwo distinguishable sub-populations of cells in a total population ofcells; (b) dividing the sample into at least two parts; (c) incubatingat least one part obtained in step (b) in the absence of a test compoundand at least one part obtained in step (b) in the presence of a testcompound; (d) determining the number of cells in one of the at least twosub-populations that exhibit a distinguishable phenotype, relative tothe number of cells in the total population of cells that exhibit thesame phenotype in (i) the at least one part incubated in the presence ofthe test compound and (ii) in the at least one part incubated in theabsence of the test compound; and (e) determining selectivity of thetest compound to induce the phenotype referred to in (d) in the one subpopulation referred to in step (d) over all other subpopulations bydividing (i) through (ii) wherein the test compound selectively inducesthe phenotype referred to in (d) if (i) divided through (ii) is greaterthan 1, preferably greater than 1.05, 1.1, 1.5, 2, 3 most preferably 5,and selectively inhibits or reduces the phenotype referred to in (d) ifit is less than 1, preferably less than 0.95, 0.9, 0.7, 0.5, 0.3, mostpreferably less than 0.2.
 2. The method according to claim 1, whereinthe distinguishable phenotype in step (d) is viability and wherein (i)if the selectivity determined in step (e) is <1 the test compound isdetermined to selectively reduce the number of viable cells of the onesub-population of step (d), and (ii) if the selectivity determined instep (e) is >1 the test compound is determined to selectively improveviability of the one sub-population and/or to selectively reduce theviability of one or more of the sub-population(s) other than the onesub-population of step (d).
 3. A method for determining whether asubject suffering from cancer will respond or is responsive to treatmentwith a test compound, the method comprising the steps: (a) providing asample obtained from the subject comprising at least two sub-populationsof cells in a total population cells, wherein at least onesub-population corresponds to cancerous cells and at least onesub-population corresponds to non-cancerous cells; (b) dividing thesample into at least two parts; (c) incubating at least one partobtained in step (b) in the absence of a test compound and at least onepart in the presence of a test compound; (d) determining the number ofviable cells in at least one of the sub-populations corresponding tocancer cells relative to the number of viable cells in the totalpopulation of cells in (i) the at least one part incubated in thepresence of the test compound and (ii) the at least one part incubatedin the absence of the test compound; and (e) determining whether thesubject will respond or is responsive to treatment with the testcompound by dividing (i) through (ii), wherein the subject will respondor is responsive to treatment if the resulting value is less than 1,preferably less than 0.95, 0.9, 0.8, 0.6, 0.4 most preferably less than0.2.
 4. The method of claim 3, wherein the method is repeated for atleast two test compounds and whether the subject will respond or isresponsive to treatment with a combination of the at least two testcompounds is determined by subtracting the values obtained in (e) foreach of the at least two test compounds from 1.0, and summing over theresulting values for the at least two test compounds wherein if theresulting sum is greater than −1, preferably greater than −0.5, 0, 0.5,most preferably greater than 1, the subject is determined to respond orbe responsive to treatment with the combination of the at least two testcompounds.
 5. The method according to claim 1, wherein the testcompound(s) comprise(s) one or more chemical substances.
 6. The methodaccording to claim 1, wherein at least one part obtained in step (b) isfurther divided into at least two parts, wherein each of the at leasttwo parts is incubated in step (c) with the test compound at differentconcentrations and wherein steps (d) and (e) are repeated for eachconcentration of the test compound independently to determine aselectivity/value at each concentration of the test compound whereby anaverage selectivity/value over all concentrations is calculated afterstep (e) and used for determining the final selectivity/value.
 7. Themethod according to claim 1, wherein in step (b) the sample is dividedinto at least three parts and in step (c) at least two parts areincubated in the absence of a test compound and/or at least two partsare incubated in the presence of a test compound whereby each partincubated in the presence of the test compound is incubated in thepresence of the same concentration of the test compound, and wherein instep (d) the number of cells in the one of the at least twosub-populations that exhibit a distinguishable phenotype relative to thenumber of cells in the total population of cells that exhibit the samedistinguishable phenotype is determined for (i) each part incubated inthe presence of the test compound independently and/or (ii) each partincubated in the absence of the test compound independently and theaverage of the relative numbers obtained in (i) and/or the average ofthe relative numbers obtained in (ii) is used.
 8. The method accordingto claim 1, wherein in step (b) the sample is divided into at leastthree parts and in step (c) at least one part is incubated in theabsence of a test compound and/or at least two parts are incubated inthe presence of at least two different concentrations of the testcompound and in step (d) the number of cells in the one of the at leasttwo sub-populations that exhibit a distinguishable phenotype relative tothe number of cells in the total population of cells that exhibit thesame distinguishable phenotype is determined for (i) each part incubatedin the presence of the test compound independently and/or (ii) each partincubated in the absence of the test compound independently wherein theaverage of (i) is determined for each concentration independently and/orthe average of (ii) is determined and used for further steps and whereinin step (e) the selectivity/value is determined for each concentrationof the test compound by dividing the average of (i) for eachconcentration through the average of (ii) and the finalselectivity/value is obtained by averaging the selectivity/value foreach concentration.
 9. The method according to claim 3, wherein themethod is repeated for at least two test compounds and the test compoundwith the lowest value obtained in step (e) is selected for treatment ofthe subject suffering from cancer.
 10. The method according to claim 4,wherein the method is repeated for at least three test compounds and thecombination of at least two of the at least three test compounds withthe highest value obtained by subtracting the values obtained in (e) foreach of the at least two test compounds in the combination from 1.0, andsumming over the resulting values for the at least two test compounds inthe combination, is selected for treatment of the subject suffering fromcancer.
 11. The method according to claim 3, wherein the cancer is acancer associated with PBMCs or bone marrow cells or cells derived fromPBMCs or bone marrow cells.
 12. The method according to claim 1, whereinthe sample is a tissue sample that contains at least 1% cancerous cellsand/or at least 1% non-cancerous cells.
 13. The method according toclaim 12, wherein the tissue sample is cultured as a non-adherent cellmonolayer.
 14. The method according to claim 13, wherein the number ofviable cancerous and non-cancerous cells is determined using automatedmicroscopy.
 15. The method according to claim 14, wherein the number ofviable cells is determined as the number of non-fragmented nuclei.